Keywords c

C-Means Clustering Section: Fuzzy Clustering, Fuzzy Classification Techniques, Fuzzy C-Means (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

CAD Definition:* Computer Assisted Design. Computer Assisted Diagnosis. A variety of meanings, depending on context.
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Graphics and CAD Based Vision, CAD Models (H1)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* CAD-Based 3D Object Representation for Robot Vision
* CAGD Based Computer Vision
* Organizing Large Structural Modelbases
* Precompiling a Geometric Model into an Interpretation Tree for Object Recognition in Bin-Picking Tasks
8 for CAD

CAD, Survey Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* CAD-Based Robot Vision

Cadastral Data Section: GIS: Cadastral Data Storage and Use (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Calcification Section: Mammography, Microcalcifications, Detection, Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Calibration Object Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration Using Calibration Object, or Known Features (H2)

Calibration Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Calibration -- Laser Scanner Multi-Path, Multipath (H4)
Section: Calibration -- LiDAR, Laser Scanner, Depth Sensor, Scanner Error Analysis (H3)
Section: Camera Calibration FengYun-3, FY-3, FY-4 (H2)
Section: Camera Calibration Techniques (H1)
Section: Camera Calibration ZY-3, ZiYuan-3 (H2)
Section: Camera Calibration, Perspective N Point Problem (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Laser Scanner Calibration -- Calgary Group, Lichti (H4)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Radar Calibraion (H3)
Section: RGB-D Laser Scanner Calibration, Color and LIDAR (H4)
* Multi-View AAM Fitting and Camera Calibration
14 for Calibration

Calibration, Range Finder Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Projective Calibration of a Laser-Stripe Range Finder

Calibration, Self Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Self Calibration, Autocalibration, Auto-Calibration (H2)
Section: Camera Calibration, Stereo, Robot Based, Movable (H3)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Critical Motions and Ambiguous Euclidean Reconstructions in Auto-Calibration
* Multiview Geometry: Profiles and Self-Calibration
7 for Calibration, Self

Calibration, Stereo Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Self-Calibration of an Uncalibrated Stereo Rig from One Unknown Motion

Camera Calibration Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Atmospheric Corrections for Remote Sensing, Satellite and Space Images (H3)
Section: Calibration Using Line Features, Lines (H3)
Section: Camera Calibration FengYun-3, FY-3, FY-4 (H2)
Section: Camera Calibration Techniques (H1)
Section: Camera Calibration Using Calibration Object, or Known Features (H2)
Section: Camera Calibration ZY-3, ZiYuan-3 (H2)
Section: Camera Calibration, Lens Distortion, Aberration, Radial Distortion, Internal Parameters (H2)
Section: Camera Calibration, Perspective Based, Vanishing Points (H2)
Section: Camera Calibration, Perspective N Point Problem (H3)
Section: Camera Calibration, Photogrammetric, Bundle Adjustment, Block Adjustment (H2)
Section: Camera Calibration, Robot Based, Servo (H2)
Section: Camera Calibration, Self Calibration, Autocalibration, Auto-Calibration (H2)
Section: Camera Calibration, Stereo, Robot Based, Movable (H3)
Section: Camera Calibration, Stereo (H2)
Section: Camera Orientation Computations, Camera Calibration, Interior Orientation, Exterior Orientation (H2)
Section: Camera Pose (H2)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Catadioptric, Omnidirectional Camera Calibration, Fisheye Lens (H3)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Photometric Calibration, Radiometric Calibration, Spectral Calibration, Color Calibration (H2)
Section: Pushbroom Camera Calibration Issues (H3)
Section: Radiometric Calibration of Remote Sensing, Satellite and Space Images (H3)
Section: Refractive, Water, Underwater Camera Calibration (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Section: Vignetting Correction, Vignetting Analysis (H3)
Section: Weakly Calibrated Cameras (H1)
Section: Zoom Lens Calibration, Focal Lengths (H3)
* Bundle Adjustment with Object Space Constraints for Site Modeling
* Canonic Representations for the Geometries of Multiple Projective Views
* Effects of Camera Alignment Errors on Stereoscopic Depth Estimates
* Multiple View Geometry in Computer Vision
* On The Optimization Criteria Used in Two-View Motion Analysis
* Techniques for Calibration of the Scale Factor and Image Center for High Accuracy 3-D Machine Vision Metrology
* Visually Estimating Workpiece Pose in a Robot Hand Using the Feature Points Method
38 for Camera Calibration

Camera Calibration, Distortion Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Lens Distortion, Aberration, Radial Distortion, Internal Parameters (H2)

Camera Calibration, Focal Length Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Zoom Lens Calibration, Focal Lengths (H3)

Camera Calibration, Laser Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Calibration -- LiDAR, Laser Scanner, Depth Sensor, Scanner Error Analysis (H3)

Camera Calibration, Motion Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Robot Based, Servo (H2)
Section: Camera Calibration, Stereo, Robot Based, Movable (H3)

Camera Calibration, Perspective Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Perspective Based, Vanishing Points (H2)

Camera Calibration, Radiometric Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Atmospheric Corrections for Remote Sensing, Satellite and Space Images (H3)
Section: Photometric Calibration, Radiometric Calibration, Spectral Calibration, Color Calibration (H2)
Section: Radiometric Calibration of Remote Sensing, Satellite and Space Images (H3)

Camera Calibration, Robot Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Robot Based, Servo (H2)

Camera Calibration, Stereo Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Calibration, Stereo, Robot Based, Movable (H3)
Section: Camera Calibration, Stereo (H2)

Camera Fingerprint Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Source Camera Identification, Camera Fingerprint (H3)

Camera Following Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Target Tracking, Active, Camera Following, Real Time Issues, Hardware (H3)

Camera Identification Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Source Camera Identification, Camera Fingerprint (H3)

Camera Motion Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Building mosaics from video using MPEG motion vectors

Camera Networks Section: Camera Networks for Surveillance (H4)
Section: Hardware, Sensor and Camera Arrangements for Surveillance Systems (H3)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)

Camera Orientation Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Orientation Computations, Camera Calibration, Interior Orientation, Exterior Orientation (H2)

Camera Pose Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Pose (H2)

Camera, Conical Mirror Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Real-Time Generation of Environmental Map and Obstacle Avoidance Using Omnidirectional Image Sensor with Conic Mirror

Camera, Spherical Mirror Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Feature Matching in 360^o Waveforms for Robot Navigation
* Image-Based Navigation Using 360^o Views

Camera, Variable Focus Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Obtaining Focused Images Using a Non-frontal Imaging Camera

Cameras Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Optical Sensors for Machine Vision (H2)
Section: Sensors for Machine Vision, Image Sensors (H1)

Camouflage Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Camouflaged Object Detection, Camouflage (H3)

Cancelable Fingerprint Section: Cancelable Fingerprint Template, Recognition, Analysis, Systems (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)

Cancer Detection Section: Medical Applications -- Cancer Diagnosis and Analysis (H1)
Section: Medical Applications -- Cervical Cancer Analysis, Ovarian Cancer (H2)
Section: Medical Applications -- Lymph Nodes (H2)
Section: Medical Applications -- Prostate Cancer Analysis (H2)
Section: Medical Applications -- Skin Cancer, Melanoma (H2)
Section: Medical Applications -- Thyroid (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
7 for Cancer Detection

Canny Edges Section: Directional Masks, Gaussian Masks, Canny etc. (H2)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)

Canola Section: Rapeseed Crop Analysis, Canola Analysis, Production, Detection (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Canonical Views Section: Aspect Graph Matching, Characteristic Views (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)

Canopy Height Section: Canopy Height Measurement (H4)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Forest Analysis, Canopy Heights, LiDAR (H4)

Canopy Water Section: Canopy Water Content (H3)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)

Canopy Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Trees, Forest Canopy Analysis (H3)

Capsule Network Section: Capsule Networks (H4)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

CAPTCHA Section: Completely Automated Public Turing Test to Tell Computers and Humans Apart, CAPTCHA, Generation, Breaking (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Breaking reCAPTCHAs with Unpredictable Collapse: Heuristic Character Segmentation and Recognition
* CAPTCHA Challenge Tradeoffs: Familiarity of Strings versus Degradation of Images
* ScatterType: a legible but hard-to-segment CAPTCHA

Captioning Section: Annotation, Captioning, Image Captioning (H2)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Multi-Modal, Cross-Modal Captioning, Image Captioning (H3)
Section: Transformer for Captioning, Image Captioning (H3)
Section: Video Retrieval, Video Annotation, Video Categorization, Genre (H4)

Captions Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Video Analysis -- Captions, Text, Video Text (H3)

Car Following Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Car Following Control, Leader-Follower Control (H4)

Carbon Dioxide Section: Pollution, CO2 Measurements, Carbon Dioxide, Carbon Monoxide (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Carbon Monoxide Section: Pollution, CO2 Measurements, Carbon Dioxide, Carbon Monoxide (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Carbon Sequestration Section: Carbon Sequestration, CO2 Sequestration, Carbon Storage (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Carbon Storage Section: Carbon Sequestration, CO2 Sequestration, Carbon Storage (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Carbon Section: Carbon Sequestration, CO2 Sequestration, Carbon Storage (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Soil Organic Carbon (H2)

Carciac Section: Cardiac Electrophysiology (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Cardiac CT Section: Heart, Cardiac, Angiography using CAT, CT, Tomography (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Cardiac Motion Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Tracking Applied to Heart Images (H3)

Cardiac MRI Section: Heart, Cardiac Analysis using MRI Analysis, Cardiac MRI (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Cardiac Ultrasound Section: Heart, Cardiac, Echocardiography, Ultrasound (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Cardiac Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Deformable Models, Cardiac Motion Models for Volumes, Left Ventricle (H3)
Section: Medical Applications -- Heart, Cardiac Applications (H1)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Cargo Inspection Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Surveillance Systems, Applied to Baggage Inspection, Cargo Inspection (H3)

Carotid Artery Section: Medical Applications -- Coronary Arteries, Carotid Arteries (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Carried Objects Section: Carried Objects, Carrying Objects (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)

Cartography Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: CMU MAPS Image Database System (H1)
Section: Evaluation, Quality AssissmentPansharpening (H4)
Section: General Cartography, Remote Sensing Issues (H1)
Section: Image and Sensor Fusion for Cartography and Aerial Images, Satellite Images, Remote Sensing (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Pansharpening, Fusion of Aerial Images (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: SRI General Cartography Systems (H1)
Section: Workshops -- Mapping, Cartography, Urban Models, Remote Sensing (H3)
* Knowledge-Based Aerial Photo Interpretation
* Learning to Detect Rooftops in Aerial Images
* Marco: Map Retrieval by Content
* Rule Based Interpretation of Aerial Imagery
* Semi-Automated Object Measurement Using Multiple-Image Matching from Mobile Mapping Image Sequences
18 for Cartography

Cartoon Segmentation Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Cartoon Plus Texture Segmentation, Cartoon-Texture Segmentation (H3)

Cartoons Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Speech Ballons in Comics, Comic Analysis, Panel Detection (H4)

Cascade Classifier Section: Hierarchical Combination, Multi-Stage Classifiers (H4)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Castings Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Metal Inspection, Castings, Machining (H3)

CAT Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Tomographic Image Generation, CAT, CT, Reconstruction (H2)
Section: Tomographic Images, CAT Scans (Computed Axial Tomography) (H1)
Section: Tomographic Images, CAT, CT, Overviews, Surveys, Datasets (H2)
Section: Tomographic Object Construction, Object Extraction, Analysis, Organs (H2)

Catadioptric Calibration Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Catadioptric, Omnidirectional Camera Calibration, Fisheye Lens (H3)

Catadioptric Camera Section: Catadioptric Cameras (H4)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Epipolar geometry of catadioptric stereo systems with planar mirrors

Catadioptric Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Catadioptric, Omnidirectional Camera Calibration, Fisheye Lens (H3)

Cataract Section: Cataracts, Detection, Analysis, Surgery (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Caves Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Specific 3-D Models, Rock Art, Petroglyphs, Rock Structures, Caves (H2)

CBIR Section: Document Retrieval Systems, Databases and Issues, Libraries (H2)
Section: Image Database -- Overall Systems (H2)
Section: Image Database Applications, Content Based Image Retrieval (H1)
Section: Image Database, Retrieval -- Surveys, Evaluations (H2)
Section: Image Retrieval, Libraries, Databases, Multimedia (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
7 for CBIR

CCA Definition:* Canonical Correlation Analysis.

Cell Extraction Section: Extraction and Analysis of Cells (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Cell Nucleus Section: Cell Nucleus, Cell Nuclei Analysis, Detection (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Cell Phone Section: Cell Phone Transmission Issues, 5G, 6G (H3)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)

Cell Segmentation Section: Extraction and Analysis of Cells (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Cell Tracking Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Tracking Cells, Deformations, Motion, Real-Time Analysis (H3)

Cells Section: 3-D Cell Analysis (H3)
Section: Blood Cell Cancers, Lymphoma, Leukemia (H3)
Section: Blood Cells, Counting, Extraction, Analysis (H2)
Section: Cell Nucleus, Cell Nuclei Analysis, Detection (H3)
Section: Extraction and Analysis of Cells (H2)
Section: Malaria Detection, Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Surveys, Comparisons, Cells, DNA (H2)
Section: Tracking Cells, Deformations, Motion, Real-Time Analysis (H3)
9 for Cells

Cellular Automata Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Multi-Processor Algorithms, Multi-Core, Cellular, Systolic (H2)
* Parallel Image Processing by Memory-Augmented Cellular Automata

Cellular Networks Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Mobile, Cellular, LTE, Tranmission (H4)

Cerebral Aneurysm Section: Brain, Cortex, Cerebral Arteries, Cerebral Aneurysm, Cerebrovascular (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Cervical Cancer Section: Medical Applications -- Cervical Cancer Analysis, Ovarian Cancer (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

CH4 Section: Pollution, Methane Measurements, CH4, Other Hydrocarbons (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Chain Codes Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Chain Code Representations (H3)
Section: Curve Partitions, Applied to Chain Codes (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Chain-Link Compression of Arbitrary Black-White Images
* Chaincode Contour Processing for Handwritten Word Recognition
* On Limit Properties in Digitization Schemes
* On the Encoding of Arbitrary Geometric Configurations
9 for Chain Codes

Chain Codes, Evaluation Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Analysis of the Precision of Generalized Chain Codes for the Representation of Planar Curves

Chain Codes, Survey Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Computer Processing of Line Drawing Images

Chamfer Matching Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Chamfering: A fast method for obtaining approximations of the Euclidean distance in N dimensions
* Fast directional chamfer matching
* Parametric Correspondence and Chamfer Matching: Two New Techniques for Image Matching

Change Detection Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Applied Change Analysis, Specific Site Applications, Site Specific Temporal (H2)
Section: Building Change Detection (H4)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Change Detection -- Image Level (H2)
Section: Change Detection for Damage Assessment (H3)
Section: Change Detection for Hyperspectral Images (H3)
Section: Change Detection for Remote Sensing Image Level (H3)
Section: Change Detection, Urban Area Land Cover, Temporal Analysis (H3)
Section: Changes using Landsat Images (H4)
Section: Erosion Analysis, Changes (H2)
Section: Forest Change Evaluation, Change Detection, Temporal Analysis (H3)
Section: Forest Disturbance, Regeneration, Regrowth (H3)
Section: Forest Storm Damage Assessment, Wind Throw (H4)
Section: Land Cover Change Analysis Using Learning, Neural Nets (H3)
Section: Land Cover Change Analysis, Global Changes, Global Analysis (H3)
Section: Land Cover Change Analysis, Remote Sensing Change Analysis, Temporal Analysis (H2)
Section: Land Cover Change Analysis, Seasonal, Annual Variations, Climate Change, Analysis (H3)
Section: Land Cover Change Analysis, Temporal Analysis, Specific Site, China (H3)
Section: Land Cover, Land Use Change Analysis for Radar and SAR (H4)
Section: Land Use Change Analysis (H3)
Section: Long Term Changes, Climate Change, Analysis (H4)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Misregistration Errors, Evaluation Change Detection (H3)
Section: NDVI, Normalized Difference Vegetation Index, Changes (H3)
Section: Night Time Image Analysis for Urban Area Detection, Change and Growth (H3)
Section: Pasture, Grassland, Rangeland, Change, Degradation, Temporal (H4)
Section: Plant Disease Analysis, General Plant Diseasses (H3)
Section: Radar, SAR Image Change Detection (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Shore Line Changes, Erosion (H3)
Section: Site Model Change Detection, Map Update (H3)
Section: Tundra Regions, Permafrost Analysis (H2)
Section: Very High Resolution Land Cover Change Analysis (H3)
* Automatic Comparison of a Topographic Map with Remotely-Sensed Images in a Map Updating Perspective: The Road Network Case
* Change Detection and Analysis in Multi-Spectral Images
* Detecting Changes in Aerial Views of Man-Made Structures
* Fast Structure-Adaptive Evaluation of Local Features in Images, A
* Model Validation for Change Detection
* Optimum Multisensor Data Fusion for Image Change Detection
* Quantitative Measures of Change Based on Feature Organization: Eigenvalues and Eigenvectors
* Segmentation Characterization for Change Detection
* Standardized Radiometric Normalization Method for Change Detection Using Remotely Sensed Imagery, A
* Symbolic Image Registration and Change Detection
46 for Change Detection

Change Detection, Differencing Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Algorithm for Estimating Small Scale Differences Between Two Digital Images, An
* Computer Comparison of Pictures
* Novel Change Detection Algorithm Using Adaptive Threshold, A
* Site-Model-Based Change Detection and Image Registration
* Techniques for Change Detection
7 for Change Detection, Differencing

Character Recognition Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Arabic Numbers, Digits, Handwritten, Numeral Recognition (H3)
Section: Character Recognition Survey, Overview, Evaluations (H2)
Section: Character Recognition Systems (H1)
Section: Chinese Characters, Japanese Characters, Handwritten (H3)
Section: Chinese Characters, Using Stroke and Radical Analysis, Features (H3)
Section: Chinese, Japanese and Kanji Characters (H2)
Section: Documents and Character Analysis -- Surveys, Comparisons, Evaluations (H1)
Section: General Character Recognition Issues (H2)
Section: Hidden Markov Models, HMM (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Multiple Classifiers Applied to Arabic Numbers (H4)
Section: Neural Networks for Numbers and Digits (H4)
Section: OCR Evaluations (H2)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Online Recognition of Chinese Characters (H3)
Section: Other Character Sets (H2)
Section: Roman Alphabet (H2)
* Adaptive Algorithm for Text Detection from Natural Scenes, An
* Fuzzy Pyramid Scheme for Distorted Object Recognition
* Hexagonal Wavelet Representations for Recognizing Complex Annotations
* Image Thresholding for Optical Character Recognition and Other Applications Requiring Character Image Extraction
* Scene Text Extraction and Translation for Handheld Devices
23 for Character Recognition

Characteristic Views Section: Aspect Graph Matching, Characteristic Views (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)

Charging Stations Section: Charging Station Placement, Schedulding, Scaling (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)

Charging Section: Charging Station Placement, Schedulding, Scaling (H4)
Section: Electric Vehicle Issues, Usage, Charging, Controls (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Pricing Issues in Charging (H4)
Section: Transit, Bus, Electric Vehicle Issues (H4)
Section: Wireless Power, Wireless Charging (H4)

Check Amounts Section: Money and Check Processing -- Amounts, etc. (H2)
Section: OCR, Document Analysis and Character Recognition Systems (H)

Chest X-Ray Section: Chest X-Ray Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Ribs, Chest X-Rays (H3)
Section: Tuberculosis Analysis, Tuberculosis Bacilli (H3)

Chinese Character Recognition Section: Chinese Characters, Japanese Characters, Handwritten (H3)
Section: Chinese Characters, Review, Survey, Evaluations (H3)
Section: Chinese Characters, Using Stroke and Radical Analysis, Features (H3)
Section: Chinese, Japanese and Kanji Characters (H2)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Online Recognition of Chinese Characters (H3)

Chinese Seal Recognition Section: Chinese Character Seals (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)

Chlorophyll Fluorescence Section: Chlorophyll Estimation, Chlorophyll Concentration, Chlorophyll Fluorescence, Chlorophyll Index (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Chlorophyll Section: Chlorophyll Estimation in Water (H3)
Section: Chlorophyll Estimation, Chlorophyll Concentration, Chlorophyll Fluorescence, Chlorophyll Index (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Chromosomes Section: Chromosome Analysis and Extraction, Genome (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Circle Detection Section: Circular Features, Circle Detection, Circle Fitting, or Particular Curves (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Randomized circle detection with isophotes curvature analysis

Circle Fitting Section: Circular Features, Circle Detection, Circle Fitting, or Particular Curves (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)

Circle Generation Section: Circle Generation (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)

Circles Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Basic Algorithms to Partition Curves, Represent Curves (H2)
Section: Circle Generation (H3)
Section: Circular Features, Circle Detection, Circle Fitting, or Particular Curves (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Hough Transform -- Circle Features (H2)
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Bayesian Method for Fitting Parametric and Nonparametric Models to Noisy Data, A
* Original Approach for Extracting Circular Shapes from Technical Charts, An
9 for Circles

Circular Features Section: Circle Generation (H3)
Section: Circular Features, Circle Detection, Circle Fitting, or Particular Curves (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)

Citrus Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Citrus Trees, Orchards, Diseases (H4)

City Models Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Large Scale Models, City Scale Models, City Models (H2)

City Section: GIS Implementation, City Models, Urban Models, City Data (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

CityGML Section: CityGML (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Clarity Section: Coastal Water Quality, Water Clarity (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Water Clarity (H3)

Classifer Combinations Section: Bagging, Combinations, Classifiers (H4)
Section: Classifier Combination, Evaluation, Overview, Appliction Specific (H4)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Hierarchical Combination, Multi-Stage Classifiers (H4)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Voting for Combinations, Classifiers (H4)
* Multiple classifier combination for face-based identity verification
7 for Classifer Combinations

Classification Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Algal Blooms, Analysis, Detection (H2)
Section: Classification for Crops, Analysis of Production, Specific Crops, Specific Plants (H2)
Section: Classification for Urban Area Land Cover, Remote Sensing (H2)
Section: Classification Methods, Clustering for Region Segmentation (H2)
Section: Clustering Techniques, Pattern Recognition Techniques (H1)
Section: Clustering, Pattern Recognition, General Issues (H2)
Section: Cotton, Analysis and Change (H3)
Section: Cyanobacteria, Analysis, Detection (H3)
Section: Dryland Analysis and Change, Arid Regions (H4)
Section: Feature Selection in Pattern Recognition or Clustering (H2)
Section: Floodplains, Riverside (H3)
Section: Ice Detection, Glaciers Detection and Analysis (H1)
Section: K-Means Clustering (H2)
Section: King Sun Fu Pattern Recognition Papers (H2)
Section: Land Cover Analysis, Specific Location Applications, Site Analysis, Site Specific (H1)
Section: Land Cover Analysis, Specific Site North America (H2)
Section: Land Cover Analysis, Specific Site, China (H2)
Section: Land Cover Analysis, Water Detection, Water Areas, Water Body (H1)
Section: Land Cover Change Analysis Using Learning, Neural Nets (H3)
Section: Land Cover Change Analysis, Remote Sensing Change Analysis, Temporal Analysis (H2)
Section: Land Cover Change Analysis, Seasonal, Annual Variations, Climate Change, Analysis (H3)
Section: Land Cover Change Analysis, Temporal Analysis, Specific Site, China (H3)
Section: Land Cover, General Problems, Remote Sensing (H1)
Section: Land Cover, Land Use Change Analysis for Radar and SAR (H4)
Section: Land Surface Temperature, Remote Sensing (H2)
Section: LiDAR for Land Cover, Laser Scanners for Land Cover, Remote Sensing (H2)
Section: Long Term Changes, Climate Change, Analysis (H4)
Section: Maize or Corn Crop Analysis, Production, Detection, Health, Change (H3)
Section: Marsh, Marsh Detection, Analysis (H3)
Section: Nearest Neighbor Classification (H2)
Section: Neural Networks for Classification and Pattern Recognition (H3)
Section: Other Soil Properties, Remote Sensing (H2)
Section: Pasture, Grassland, Rangeland Analysis (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Peatland, Analysis and Change (H3)
Section: Potato Crop Analysis, Production, Detection, Health, Change (H3)
Section: Projection Learning (H3)
Section: Radar for Land Cover, SAR for Land Cover, Remote Sensing (H2)
Section: Rapeseed Crop Analysis, Canola Analysis, Production, Detection (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Rice Crop Analysis, Production, Detection, Health, Change (H3)
Section: Sentinel-1, -2, -3 for Land Cover, Remote Sensing (H3)
Section: Shore Line Changes, Erosion (H3)
Section: Shore Line Detection, Analysis along Shore Line (H2)
Section: Soil Moisture, SMAP, Soil Moisture Active Passive, Remote Sensing (H2)
Section: Soybean Crop Analysis, Beans, Production, Detection, Health, Change (H3)
Section: Sparse Feature Selection (H3)
Section: Statistical Learning, Clustering, Learning Feature Values (H2)
Section: Sugar Cane Crop Analysis, Production, Detection, Health, Change (H3)
Section: Tidal Areas, Inter-Tidal, Coastal, Wetlands, Wetland Detection, Analysis (H3)
Section: Very High Resolution Land Cover Change Analysis (H3)
Section: Vineyard Analysis, Viticulture, Grapes, Production, Detection, Health, Change (H3)
Section: Water Quality, Turbidity, Water Areas (H2)
Section: Wetlands, Wetland Detection, Analysis (H2)
Section: Wheat Crop Analysis, Detection, Change (H3)
* Performance Evaluation of Multispectral Analysis for Surface Material Classification
57 for Classification

Classification, 3-D Data Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Point Cloud Classification (H3)

Classifier Combinations Section: Fusion for Multiple Classifiers (H4)
Section: Mixture of Experts, Multiple Classifiers, Combining Classifiers (H4)
Section: Multiple Classifiers, Combining Classifiers, Combinations (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Classifier Ensembles Section: Fusion for Multiple Classifiers (H4)
Section: Mixture of Experts, Multiple Classifiers, Combining Classifiers (H4)
Section: Multiple Classifiers, Combining Classifiers, Combinations (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Classifiers, multiple Section: OCR, Document Analysis and Character Recognition Systems (H)
* Generalized-Approach to the Recognition of Structurally Similar Handwritten Characters Using Multiple Expert Classifiers

Classroom Environment Section: Human Action Recognition, Indoor Environments, Classroom, Smart Room (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)

Climate Change Section: Climate Data (H2)
Section: Land Cover Change Analysis, Global Changes, Global Analysis (H3)
Section: Land Cover Change Analysis, Seasonal, Annual Variations, Climate Change, Analysis (H3)
Section: Long Term Changes, Climate Change, Analysis (H4)
Section: NDVI, Normalized Difference Vegetation Index, Changes (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* Primary Production, an Index of Climate Change in the Ocean: Satellite-Based Estimates over Two Decades
7 for Climate Change

Climate Zones Section: Climate Zones (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Climate Section: Climate Data (H2)
Section: Land Cover Change Analysis, Seasonal, Annual Variations, Climate Change, Analysis (H3)
Section: Long Term Changes, Climate Change, Analysis (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

CLIP Section: CLIP, Contrastive Language-Image Pre-Training (H4)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)

Clock Drift Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: GPS, GNSS Network, Bias, Clock Drift (H4)

Close Range Photogrammetry Section: Automated Measurement Systems, Close Range Photogrammetry (H2)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)

Closest Point Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Closest Point Algorithms, ICP, Iterative Closest Point (H3)

Cloth Changing Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Re-Identification, Cloth-Changing, Clothes Changing (H4)

Cloth Rendering Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Rendering, Cloth, Clothing, Fabric (H4)

Clothes Section: Clothing Styles, Fashion Related (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Human Posture and Shape, Clothing Related (H3)

Clothing Section: Clothing Try-On Systems (H4)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)

Cloud Detection Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Cloud Detection, Extraction and Removal (H2)
Section: Cloud Detection, Ground-Based (H3)
Section: Cloud Shadows, Combined Cloud and Shadow, Extraction and Removal (H2)
Section: Thin Cloud Detection and Removal (H3)

Cloud Identification Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Cloud Identification, Cloud Type, Cloud Properties (H3)

Cloud Removal Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Cloud Detection, Extraction and Removal (H2)

Cloud Shadow Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Cloud Shadows, Combined Cloud and Shadow, Extraction and Removal (H2)

Cloud Top Height Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Cloud Top Heights, Cloud-Top Analysis (H3)

Clouds Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Convective Storm Analysis, Weather Radar Applications (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Optical Flow Field Computations and Use (H)
Section: Tracking for Weather, Clouds (H3)
* Correlation-Relaxation-Labeling Framework for Computing Optical Flow: Template Matching from a New Perspective, A

Clumping Index Section: Clumping Index, Measurement, Effects (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Clustering Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Binary Clustering, Two Class Classification (H3)
Section: Classification Methods, Clustering for Region Segmentation (H2)
Section: Clustering Applications (H2)
Section: Clustering Techniques, Pattern Recognition Techniques (H1)
Section: Clustering, Classification, General Methods (H2)
Section: Clustering, Pattern Recognition, General Issues (H2)
Section: Density Based Clustering (H3)
Section: Detecting Clusters and Number of Clusters, Number of Classes (H2)
Section: Fuzzy Clustering, Cluster Validity Tests (H3)
Section: Fuzzy Clustering, Fuzzy Classification Techniques, Fuzzy C-Means (H2)
Section: Fuzzy Clustering, Overview, Summary, Comparisons (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Linear Separable Classification (H2)
Section: One Class Clustering, One Class Classification (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Unsupervised Clustering and Optimal Clusters for Segmentation (H3)
* Bottom Up Image Segmentor, A
* Image Segmentation by a Parallel, Non-Parametric Histogram Based Clustering Algorithm
* On Threshold Selection Using Clustering Criteria
* Parallel Hierarchical-Clustering Algorithms on Processor Arrays with a Reconfigurable Bus System
* Recursive Clustering Technique for Color Picture Segmentation, A
22 for Clustering

Clustering, Hierarchical Section: Iterative, Hierarchical Clustering Techniques (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Clustering, Iterative Section: Iterative, Hierarchical Clustering Techniques (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Clusters Detection Section: Detecting Clusters and Number of Clusters, Number of Classes (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Clutter Section: ATR -- Clutter, Background Issues, Noise (H2)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Target Tracking Techniques, Occlusions, Clutter (H4)
* Ratio of the Arithmetic to the Geometric Mean: A First-order Statistical Test for Multilook SAR Image Homogeneity, The

CME Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: SRI Environments -- Image Calc, CME RADIUS (H2)

CNN Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Convolutional Neural Network, CNN, Re-Identification Issues, Pedestrian Tracking (H4)
Section: Convolutional Neural Networks for Human Action Recognition and Detection (H4)
Section: Convolutional Neural Networks for Image Descriptions, Classification (H3)
Section: Convolutional Neural Networks for Object Detection and Segmentation (H4)
Section: Convolutional Neural Networks for Semantic Segmentation, CNN (H4)
Section: Convolutional Neural Networks, Design, Implementation Issues (H4)
Section: Deep Networks, Deep Learning for Human Action Recognition (H4)
Section: Efficient Implementations Convolutional Neural Networks (H4)
Section: Face Recognition Systems Using Neural Networks, Learning (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Fine-Grained Classification Using CNN, Convolutional Neural Networks (H4)
Section: Forgetting, Learning without Forgetting, Convolutional Neural Networks (H4)
Section: Human Posture, or Human Pose, Learning, Neural Networks (H3)
Section: Hyperspectral Data, Neural Networks for Classification (H4)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Incremental Learning for Human Action Recognition (H4)
Section: Inpainting, GAN, CNN, Neural Nets, Learning (H4)
Section: Intrepretation, Explaination, Understanding of Convolutional Neural Networks (H4)
Section: Learning, General Surveys, Overviews (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Neural Net Compression (H4)
Section: Neural Net Pruning (H4)
Section: Neural Net Quantization (H4)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Point Cloud Processing for Neural Networks, Convolutional Neural Networks (H3)
Section: Pooling in Convolutional Neural Networks Implementations (H4)
Section: Salient Regions, Convolutional Neural Networks, Deep Nets (H4)
Section: Single View 3D Reconstruction, Convolutional Neural Networks, CNN (H3)
Section: Single View 3D Reconstruction, Learning (H3)
Section: VQA, Visual Question Answering, Neural Networks (H4)
35 for CNN

Co-Clustering Section: Multi-View Learning, Co-Clustering (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Co-occurrence Matrix Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Co-occurrence Matrix Description Methods (H1)
* Optical Texture Analysis for Automatic Cytology and Histology: A Markovian Approach
* Statistical-Methods to Compare the Texture Features of Machined Surfaces
* Textural Features for Image Classification

Co-Salient Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Co-Salient Detection (H3)

Co-Segmentation Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Co-Segmentation, Cosegmentation (H2)

CO2 Section: Carbon Sequestration, CO2 Sequestration, Carbon Storage (H3)
Section: Pollution, CO2 Measurements, Carbon Dioxide, Carbon Monoxide (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Coast Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Shore Line Changes, Erosion (H3)

Coastal Analysis Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Coastal, Tidal Flood Analysis, Storm Surge (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Shore Line Detection, Analysis along Shore Line (H2)
Section: Tsunami Detection, Analysis, Warning, Disaster (H4)

Code Convolutional Networks Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Sequentially Aggregated Convolutional Networks

Code LPB-TOP Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* LBP-TOP: A Tensor Unfolding Revisit

Code, 3-D Segmentation * *Seg3D: Volumetric Image Segmentation and Visualization
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)

Code, 3-D Shape * *AQSENSE
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)

Code, 3-D Visualization * *map3d: Interactive scientific visualization tool for bioengineering data
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)

Code, 3D Data * *libE57: software tools for managing E57 files
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)

Code, 3D Fly Through * *Make3D
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)

Code, 3D Reconstruction Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Analysis and Implementation of a Parallel Ball Pivoting Algorithm, An

Code, 3D Vision Section: Books, Collections, Overviews, General, and Surveys (H)
* Guide to 3D Vision Computation: Geometric Analysis and Implementation

Code, 3D Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Optical Flow Field Computations and Use (H)
* Deep Meta Functionals for Shape Representation
* Order-Aware Generative Modeling Using the 3D-Craft Dataset
* PointFlow: 3D Point Cloud Generation With Continuous Normalizing Flows

Code, Action Recognition Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* CoTeRe-net: Discovering Collaborative Ternary Relations in Videos
* EAN: Event Adaptive Network for Enhanced Action Recognition
* Motion-Driven Visual Tempo Learning for Video-Based Action Recognition
* TCGL: Temporal Contrastive Graph for Self-Supervised Video Representation Learning
* Win-Fail Action Recognition
7 for Code, Action Recognition

Code, Active Appearance Model * *AAM Building
* *Active Appearance Models
* *am_tools
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)

Code, Active Blobs Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Active Blobs

Code, Active Contours Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Segmentation with Active Contours

Code, Adversarial Attack Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Spatiotemporal Attacks for Embodied Agents

Code, Affine Invariant Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* CNN-Assisted Coverings in the Space of Tilts: Best Affine Invariant Performances with the Speed of CNNs

Code, Affine Shape Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Repeatability Is Not Enough: Learning Affine Regions via Discriminability

Code, Alignment Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Cross-Domain Detection via Graph-Induced Prototype Alignment
* Fast, Approximately Optimal Solutions for Single and Dynamic MRFs

Code, Annotation Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Generating Easy-to-Understand Referring Expressions for Target Identifications
* LableMe: The Open Annotation Tool

Code, Anomaly Detection Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Graph Laplacian for image anomaly detection
* How to Reduce Anomaly Detection in Images to Anomaly Detection in Noise

Code, Artistic Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Learning to Paint With Model-Based Deep Reinforcement Learning

Code, Attention Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* MixFormer: Mixing Features across Windows and Dimensions
* Stand-Alone Inter-Frame Attention in Video Models

Code, AVU Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Open-Source Platform for Underwater Image and Video Analytics, An

Code, B-Spline Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Optimization of Image B-spline Interpolation for GPU Architectures

Code, Bilateral Filter Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Bilateral Filter for Point Clouds, The

Code, Blur Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Estimating an Image's Blur Kernel Using Natural Image Statistics, and Deblurring it: An Analysis of the Goldstein-Fattal Method

Code, Brain Lesion Segmentation * *brain lesion segmentation
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Code, Bundle Adjustment * *Simple Sparse Bundle Adjustment (SSBA)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Addingham Bundle Adjustment
* Apero, An Open Source Bundle Adjusment Software For Automatic Calibration and Orientation of Set of Images
* Design and Implementation of a Generic Sparse Bundle Adjustment Software Package Based on the Levenberg-Marquardt Algorithm, The
* Generic Bundle Adjustment Methodology for Indirect RPC Model Refinement of Satellite Imagery, A

Code, CAD Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Neural Face Identification in a 2D Wireframe Projection of a Manifold Object

Code, Calibration * *HySCaS: Hybrid Stereoscopic Calibration Software
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)

Code, Camera Calibration Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Flexible New Technique for Camera Calibration, A
* Matlab Camera Calibration Toolbox
* Versatile Camera Calibration Technique for High-Accuracy 3D Machine Vision Metrology Using Off-the-Shelf TV Cameras and Lenses, A

Code, Captioning Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Attention on Attention for Image Captioning
* Cap2Det: Learning to Amplify Weak Caption Supervision for Object Detection
* Controllable Video Captioning With POS Sequence Guidance Based on Gated Fusion Network
* Human Attention in Image Captioning: Dataset and Analysis

Code, Chain Code * *Chain Code Representation
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Fast Chain Coding of Region Boundaries

Code, Chain Code, C * *Chain Code Representation
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)

Code, Change Detection Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Detection and Interpretation of Change in Registered Satellite Image Time Series
* Image Difference Captioning With Instance-Level Fine-Grained Feature Representation

Code, Classification Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Boosting Standard Classification Architectures Through a Ranking Regularizer
* Label Relation Graphs Enhanced Hierarchical Residual Network for Hierarchical Multi-Granularity Classification
* Region-based Non-local Operation for Video Classification
* Scan: Learning to Classify Images Without Labels
* Spatially Consistent Representation Learning
7 for Code, Classification

Code, Cloud Detection Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Cloud Detection by Luminance and Inter-band Parallax Analysis for Pushbroom Satellite Imagers

Code, Clustering Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Optimized Data Fusion for Kernel k-Means Clustering

Code, CNN Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Convolution of Convolution: Let Kernels Spatially Collaborate
* Learning to Learn Parameterized Classification Networks for Scalable Input Images
* Null-sampling for Interpretable and Fair Representations
* PSConv: Squeezing Feature Pyramid into One Compact Poly-Scale Convolutional Layer
* Reduced Biquaternion Convolutional Neural Network for Color Image Processing

Code, Color Balance Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Simplest Color Balance

Code, Color Correction Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Local Color Correction

Code, Color Descriptors Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Evaluating Color Descriptors for Object and Scene Recognition

Code, Color Enhancement Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Algorithmic Analysis of Variational Models for Perceptual Local Contrast Enhancement, An
* Automatic Color Enhancement (ACE) and its Fast Implementation

Code, Color Histograms Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Image Color Cube Dimensional Filtering and Visualization

Code, Colorization Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* DeOldify: A Review and Implementation of an Automatic Colorization Method

Code, Compression Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Deep Image Compression Using Decoder Side Information

Code, Computational Geometry * *CGAL: Computational Geometry Algorithms Library
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)

Code, Computer Vision * *AccelerEyes
* *FastCV
* *Fiji Image Processing Package
* *GPU4Vision
* *Handbook of Computer Vision and Applications. 3. Systems and Applications
* *OpenCV
* *OpenVidia
* *PEIPA Computer Vision Software
* *VXL
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Computer Vision and Applications: A Guide for Students and Practitioners
* Handbook of Mathematical Models in Computer Vision
* Invitation to 3-D Vision: From Images to Geometric Models, An
* MATLAB and Octave Functions Software for Computer Vision and Image Processing
* Practical Computer Vision Using C
* Robotics, Vision and Control: Fundamental Algorithms in MATLAB
17 for Code, Computer Vision

Code, Computer Vision, C++ * *VXL
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)

Code, Computer Vision, Matlab Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* MATLAB and Octave Functions Software for Computer Vision and Image Processing
* Robotics, Vision and Control: Fundamental Algorithms in MATLAB

Code, Connected Components Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Extraction of Connected Region Boundary in Multidimensional Images

Code, Contours Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Meaningful Scales Detection: An Unsupervised Noise Detection Algorithm for Digital Contours

Code, Contrast Enhancement Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Local Contrast Enhancement based on Adaptive Logarithmic Mappings

Code, Contrastive Learning Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Video-Text Representation Learning via Differentiable Weak Temporal Alignment

Code, Convex Grouping Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Robust and Efficient Detection of Salient Convex Groups

Code, Convex Hull Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Exact polyhedral visual hulls

Code, ConvNet Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* MutualNet: Adaptive Convnet via Mutual Learning from Network Width and Resolution

Code, Convolutional Networks Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* CARAFE: Content-Aware ReAssembly of FEatures
* Dynamic Block Sparse Reparameterization of Convolutional Neural Networks
* Perspective-Guided Convolution Networks for Crowd Counting
* Simple and Robust Deep Convolutional Approach to Blind Image Denoising, A
8 for Code, Convolutional Networks

Code, Convolutional Neural Nets Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* HBONet: Harmonious Bottleneck on Two Orthogonal Dimensions

Code, Convolutional Neural Networks Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Approximated Bilinear Modules for Temporal Modeling
* BAE-NET: Branched Autoencoder for Shape Co-Segmentation
* Convolutional Character Networks
* Learning Filter Basis for Convolutional Neural Network Compression
* Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis
* Weakly Aligned Cross-Modal Learning for Multispectral Pedestrian Detection
11 for Code, Convolutional Neural Networks

Code, Corner Detection Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Analysis and Implementation of the Harris Corner Detector, An

Code, Correlation * 117 Line 2D Digital Image Correlation Code Written in MATLAB, A
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)

Code, Counting * 3C-Net: Category Count and Center Loss for Weakly-Supervised Action Localization
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Counting With Focus for Free
* From Open Set to Closed Set: Counting Objects by Spatial Divide-and-Conquer
* Learning To Count Everything
7 for Code, Counting

Code, Crack Detection Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* All Terrain Crack Detector Obtained by Deep Learning on Available Databases, An
* Crack Segmentation on UAS-based Imagery using Transfer Learning

Code, CT Data Analysis * *Core Imaging Library (CIL)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)

Code, CT Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Core Imaging Library - Part I: a versatile Python framework for tomographic imaging
* Core Imaging Library - Part II: multichannel reconstruction for dynamic and spectral tomography
* Musiré: multimodal simulation and reconstruction framework for the radiological imaging sciences

Code, Curvature Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Image Curvature Microscope: Accurate Curvature Computation at Subpixel Resolution, The

Code, Curve Decomposition Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Digital Level Layers for Digital Curve Decomposition and Vectorization

Code, Curve Detection Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* TriplClust: An Algorithm for Curve Detection in 3D Point Clouds

Code, Curve Partitions Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Near-Linear Time Guaranteed Algorithm for Digital Curve Simplification Under the Fréchet Distance, A

Code, Curve Segmentation Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Nonparametric Segmentation of Curves into Various Representations

Code, Curve Smoothing Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Algorithm for 3D Curve Smoothing, An
* Non-Parametric Multi-Scale Curve Smoothing

Code, Curvilinear Structures * 2D Filtering of Curvilinear Structures by Ranking the Orientation Responses of Path Operators (RORPO)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Code, Deblurring Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Breaking down Polyblur: Fast Blind Correction of Small Anisotropic Blurs
* Spectral Pre-Adaptation for Restoring Real-World Blurred Images using Standard Deconvolution Methods

Code, Deep Learning * *Open Deep Learning Toolkit for Robotics (OpenDR)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Defensive Patches for Robust Recognition in the Physical World
* FaPN: Feature-aligned Pyramid Network for Dense Image Prediction

Code, Deep Nets Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Attribution in Scale and Space

Code, Demosaicking Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Fast C++ Implementation of Neural Network Backpropagation Training Algorithm: Application to Bayesian Optimal Image Demosaicing, A
* Gunturk-Altunbasak-Mersereau Alternating Projections Image Demosaicking
* HighEr-Resolution Network for Image Demosaicing and Enhancing
* Image Demosaicking with Contour Stencils
* Malvar-He-Cutler Linear Image Demosaicking
* Self-Similarity Driven Demosaicking
* Zhang-Wu Directional LMMSE Image Demosaicking
8 for Code, Demosaicking

Code, Denoising Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Analysis and Extension of the PCA Method, Estimating a Noise Curve from a Single Image
* Analysis and Extension of the Percentile Method, Estimating a Noise Curve from a Single Image
* Analysis and Implementation of the BM3D Image Denoising Method, Image Processing, An
* Analysis and Improvement of the BLS-GSM Denoising Method, An
* Chambolle's Projection Algorithm for Total Variation Denoising
* DCT image denoising: a simple and effective image denoising algorithm
* Fully Convolutional Pixel Adaptive Image Denoiser
* implementation and detailed analysis of the K-SVD image denoising algorithm, An
* Implementation of a Denoising Algorithm Based on High-Order Singular Value Decomposition of Tensors
* Implementation of Image Denoising based on Backward Stochastic Differential Equations
* Noise Clinic: a Blind Image Denoising Algorithm, The
* Non-local Means Denoising
15 for Code, Denoising

Code, Depth Denoising Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Self-Supervised Deep Depth Denoising

Code, Depth from Focus Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Rational Filters for Passive Depth from Defocus

Code, Depth from Motion Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Exploiting Temporal Consistency for Real-Time Video Depth Estimation

Code, Dermatology Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Joint Acne Image Grading and Counting via Label Distribution Learning

Code, Detection Transformer Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Accelerating DETR Convergence via Semantic-Aligned Matching

Code, Distance Transform Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Distance Transforms of Sampled Functions
* Streaming Distance Transform Algorithm for Neighborhood-Sequence Distances, A

Code, Distortion Correction Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Automatic Lens Distortion Correction Using One-Parameter Division Models

Code, DNN Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Deep Decomposition Learning for Inverse Imaging Problems

Code, Document Analysis * *Gamera project
Section: OCR, Document Analysis and Character Recognition Systems (H)
* SCRIBO Module of the Olena Platform: A Free Software Framework for Document Image Analysis, The

Code, Domain Adaption Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Domain Adaptation for Semantic Segmentation With Maximum Squares Loss
* Drop to Adapt: Learning Discriminative Features for Unsupervised Domain Adaptation
* Larger Norm More Transferable: An Adaptive Feature Norm Approach for Unsupervised Domain Adaptation
* Semi-Supervised Domain Adaptation via Minimax Entropy
* Temporal Attentive Alignment for Large-Scale Video Domain Adaptation

Code, Domain Generalization Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Study of RobustNet, a Domain Generalization Method for Semantic Segmentation, A

Code, Drone Control * *Flightmare
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Learning High-Speed Flight in the Wild

Code, Drones Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* Deep Drone Acrobatics

Code, Edge Detection * *Edison: Edge Detection and Image SegmentatiON system
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Combined Corner and Edge Detector, A
* Contours, Corners and T-Junctions Detection Algorithm
* Global Measures of Coherence for Edge Detector Evaluation
* Logical/Linear Operators for Image Curves
* Recursive Filtering and Edge Tracking: Two Primary Tools for 3D Edge Detection
* Structured edge detection toolbox
* Susan: A New Approach to Low-Level Image-Processing
* Unsupervised Smooth Contour Detection
11 for Code, Edge Detection

Code, Egocentric Actions Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* What Would You Expect? Anticipating Egocentric Actions With Rolling-Unrolling LSTMs and Modality Attention

Code, Ellipse Fitting Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Ellipse Fitting for Computer Vision: Implementation and Applications
* Ellipse-Specific Direct Least-Square Fitting

Code, Emotion Analysis Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* MixedEmotions: An Open-Source Toolbox for Multimodal Emotion Analysis

Code, Energy Minimization Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Computing geodesics and minimal surfaces via graph cuts

Code, Epidemic Model Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* Compartmental Epidemiological Model Applied to the Covid-19 Epidemic, A

Code, Equalization Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Non-uniformity Correction of Infrared Images by Midway Equalization

Code, Evaluation Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Learning to Evaluate Perception Models Using Planner-Centric Metrics

Code, Event Camera Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Video to Events: Recycling Video Datasets for Event Cameras

Code, Events Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Bridging the Gap between Events and Frames through Unsupervised Domain Adaptation

Code, Explaination Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations

Code, Eye Fixation * *PeyeMMV.
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)

Code, Eye Tracking * *openEyes
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)

Code, Face Analysis Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Capturing facial videos with Kinect 2.0: A multithreaded open source tool and database
* OpenFace 2.0: Facial Behavior Analysis Toolkit
* OpenFace: An open source facial behavior analysis toolkit

Code, Face Detection * *Face Detection Home Page
* *TLD: Tracks the object, Learns its appearance and Detects
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Analysis of the Viola-Jones Face Detection Algorithm, An
* Contrario Detection of Faces with a Short Cascade of Classifiers, A

Code, Face Recognition * *Face Recogniton Home Page
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* CSU Face Identification Evaluation System: Its purpose, features, and structure, The
* FaRE: Open Source Face Recognition Performance Evaluation Package
* SeqFace: Learning discriminative features by using face sequences
* VarGFaceNet: An Efficient Variable Group Convolutional Neural Network for Lightweight Face Recognition
7 for Code, Face Recognition

Code, Face Relighting Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Face Inverse Rendering via Hierarchical Decoupling

Code, Face Tracking * *TLD: Tracks the object, Learns its appearance and Detects
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)

Code, Facial Expressions Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* AFFDEX 2.0: A Real-Time Facial Expression Analysis Toolkit
* Computer Expression Recognition Toolbox
* computer expression recognition toolbox (CERT), The

Code, Facial Landmarks Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Aggregation via Separation: Boosting Facial Landmark Detector With Semi-Supervised Style Translation
* FAB: A Robust Facial Landmark Detection Framework for Motion-Blurred Videos

Code, FastICA * *FastICA package for MATLAB, The
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)

Code, Feature Selection Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Joint Group Feature Selection and Discriminative Filter Learning for Robust Visual Object Tracking

Code, Feature Tracking Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* IntraFace

Code, Filters Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* How to Apply a Filter Defined in the Frequency Domain by a Continuous Function

Code, Flutter Shutter Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Flutter Shutter Camera Simulator, The
* Flutter Shutter Code Calculator, The

Code, Forensic Similarity Section: OCR, Document Analysis and Character Recognition Systems (H)
* Forensic Similarity for Source Camera Model Comparison

Code, Forensics, JPEG Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Reliable JPEG Quantization Table Estimator, A

Code, Forgery Detection Section: OCR, Document Analysis and Character Recognition Systems (H)
* Automatic Detection of Internal Copy-Move Forgeries in Images

Code, Forgery Section: OCR, Document Analysis and Character Recognition Systems (H)
* Image Forgery Detection via Forensic Similarity Graphs

Code, Fourier Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Shape Discrimination Using Fourier Descriptors

Code, Frame Interpolation Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Time Lens: Event-based Video Frame Interpolation

Code, Fundamental Matrix Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Fundamental Matrix of a Stereo Pair, with A Contrario Elimination of Outliers

Code, Fusion Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Structural Similarity Metrics for Quality Image Fusion Assessment: Algorithms

Code, Fusion, Matlab Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Structural Similarity Metrics for Quality Image Fusion Assessment: Algorithms

Code, Gait * *Baseline Algorithm and Performance for Gait Based Human ID Challenge Problem
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)

Code, GAN Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Transforming and Projecting Images into Class-conditional Generative Networks

Code, Gaussian Convolution Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Computing an Exact Gaussian Scale-Space
* Survey of Gaussian Convolution Algorithms, A

Code, Gaze Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Few-Shot Adaptive Gaze Estimation
* Gaze360: Physically Unconstrained Gaze Estimation in the Wild

Code, Generative Adversarial Network Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* AutoGAN: Neural Architecture Search for Generative Adversarial Networks

Code, Generative Adversarial Networks Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization

Code, Geospatial Data Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* pyjeo: A Python Package for the Analysis of Geospatial Data

Code, Geospatial * *OSGeo: Open Source Geospatial Foundation
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Code, Gesture * *HandVu Gesture Interface
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)

Code, GIS * *OSGeo: Open Source Geospatial Foundation
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Code, GNN Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* AEGNN: Asynchronous Event-based Graph Neural Networks

Code, GPU * *AccelerEyes
* *GPU4Vision
* *OpenVidia
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)

Code, Graph Embedding Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Deep Clustering by Gaussian Mixture Variational Autoencoders With Graph Embedding

Code, Graph Kernel Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* graphkit-learn: A Python library for graph kernels based on linear patterns

Code, Graph Matching Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Learning Structural Similarity of User Interface Layouts Using Graph Networks

Code, Graph Representation Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Language-Conditioned Graph Networks for Relational Reasoning
* Learning Semantic-Specific Graph Representation for Multi-Label Image Recognition

Code, Ground Visibility Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Ground Visibility in Satellite Optical Time Series Based on A Contrario Local Image Matching
* Temporal Repetition Detector for Time Series of Spectrally Limited Satellite Imagers

Code, H.264/AVC Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* H.264/AVC Refrence Software

Code, Hand Detection Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Contextual Attention for Hand Detection in the Wild

Code, HCI Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* HCI-lambda-2 Workbench: A development tool for multimodal human-computer interaction systems

Code, HDR Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Events-To-Video: Bringing Modern Computer Vision to Event Cameras
* Obtaining High Quality Photographs of Paintings by Image Fusion

Code, Head Tracking Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Fast, Reliable Head Tracking under Varying Illumination: An Approach Based on Registration of Textured-Mapped 3D Models

Code, HEIV Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* HEIV based estimation

Code, High Dynamic Range Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Analysis and Implementation of the HDR+ Burst Denoising Method, An
* Implementation of the Exposure Fusion Algorithm, An

Code, Histogram Modification Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Analysis and Implementation of the Shape Preserving Local Histogram Modification Algorithm, An

Code, Homography Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Iterative Deep Homography Estimation

Code, Hough Transform * *Hough Transform Code
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Iterative Hough Transform for Line Detection in 3D Point Clouds

Code, Hough Transform, C * *Hough Transform Code
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)

Code, HRI Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Top-1 Corsmal Challenge 2020 Submission: Filling Mass Estimation Using Multi-modal Observations of Human-robot Handovers

Code, Human Action Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* BABEL: Bodies, Action and Behavior with English Labels

Code, Human Motion Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Learning Trajectory Dependencies for Human Motion Prediction
* Predicting 3D Human Dynamics From Video
* Structured Prediction Helps 3D Human Motion Modelling

Code, Human Pose Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Learning to Reconstruct 3D Human Pose and Shape via Model-Fitting in the Loop
* Monocular 3D Human Pose Estimation by Generation and Ordinal Ranking
* Resolving 3D Human Pose Ambiguities With 3D Scene Constraints
* Single-Network Whole-Body Pose Estimation
* Tilting at windmills: Data augmentation for deep pose estimation does not help with occlusions

Code, Hyperspectral Classification Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Hyperspectral Image Classification Using Graph Clustering Methods

Code, Illumination Estimation Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Estimating natural illumination from a single outdoor image

Code, Illumination Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Camera parameters estimation from hand-labelled sun positions in image sequences

Code, Image Analysis * *C++ Template Image Processing Library
* *Core Imaging Library (CIL)
* *Delft Image Processing library, The
* *Image Processing Library 98
* *ImageLib: An Image Processing C++ Class Library
* *LibCVD: computer vision library
* *Microsoft Kinect SDK
* *MPEG Org Home Page
* *NeatVision
* *Noesis Vision
* *Recognition And Vision Library
* *Robot Vision 2 Inc.
* *Torch3vision: Machine Vision Library
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Computational strategies for protein quantitation in 2D electrophoresis gel image processor for Matlab
* Vista: A Software Environment for Computer Vision Research
18 for Code, Image Analysis

Code, Image Analysis, C * *Delft Image Processing library, The
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)

Code, Image Analysis, Matlab * *Delft Image Processing library, The
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)

Code, Image Coding Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Java-Based MPEG-4 Like Video Codec, A

Code, Image Coding, Java Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Java-Based MPEG-4 Like Video Codec, A

Code, Image Compression Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Compression Method for Arbitrary Precision Floating-Point Images, A

Code, Image Decomposition Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Cartoon + Texture Image Decomposition by the TV-L1 Model

Code, Image Decompostiong Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Directional Filters for Cartoon + Texture Image Decomposition

Code, Image Editing Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction

Code, Image Equalization Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Implementation of the Midway Image Equalization
* Midway Video Equalization

Code, Image Interpolation Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Image Interpolation with Contour Stencils
* Image Interpolation with Geometric Contour Stencils
* Linear Methods for Image Interpolation
* Roussos-Maragos Tensor-Driven Diffusion for Image Interpolation

Code, Image Matching Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Fast Affine Invariant Image Matching

Code, Image Processing * *AccuSoft
* *Bioimage Suite
* *DgiStreammer
* *FastCV
* *Fiji Image Processing Package
* *Generic Programming for Computer Vision: The VIGRA Computer Vision Library
* *GNU Image Manipulation Program
* *Groningen Image Processing System, GIPSY
* *Handbook of Mathematical Methods in Computer Vision
* *HIPR2: Free WWW-based Image Processing Teaching Materials with JAVA
* *IFS: Image File System
* *Image Processing Online
* *ImageJ-Plugins -- Various Plugins for the image manipulation software ImageJ
* *ImageJ: Image Processing and Analysis in Java
* *ImageMagick
* *IrfanView
* *JPEG 2000
* *JPEG: Joint Photographic Experts Group
* *LibTIFF: TIFF Library and Utilities
* *LTI-Lib
* *MediaCybernetics
* *Mimas
* *Mobile Robot Programming Toolkit, The
* *OpenCV
* *pbmplus Image File Format Conversion Package
* *QCV
* *Supercomputing Systems: Vision
* *Walrus Vision Toolbox
* 3-D Image Processing Algorithms
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* Algorithms for Graphics and Image Processing
* Algorithms for Image Processing and Computer Vision
* Building Imaging Applications with Java(TM)
* Computer Vision and Image Processing: A Practical Approach Using CVIPtools
* Concise Introduction to Image Processing using C++, A
* Data Structures for Image Processing in C
* Digital Image Processing Algorithms and Applications
* Digital Image Processing and Analysis: Human and Computer Vision Applications with CVIPtools, Second Edition
* Digital Image Processing Using MATLAB(R), 2nd Edition
* Digital Image Processing: A Practical Introduction Using Java
* Digital Image Processing: An Algorithmic Approach Using Java
* Digital Image Processing: An Algorithmic Approach with MATLAB
* Digital Signal and Image Processing Using MATLAB(R)
* Fundamentals of Digital Image Processing: A Practical Approach with Examples in Matlab
* Fuzzy Image Processing and Applications with MATLAB
* Handbook of Astronomical Image Processing
* Handbook of Computer Vision Algorithms in Image Algebra
* Handbook of Image Processing Operators
* High Performance Computer Imaging
* HIPS: A Unix-Based Image Processing System
* Hypermedia Image Processing Reference
* Image Analysis, Classification and Change Detection in Remote Sensing: With Algorithms for ENVI/IDL
* Image Processing Handbook, The
* Image Processing in Java
* Image Processing with MATLAB: Applications in Medicine and Biology
* Image Processing, Analysis and and Machine Vision: A MATLAB Companion
* Introduction to Image Processing Using R: Learning by Examples
* Machine Vision Algorithms in Java: Techniques and Implementation
* Pattern Recognition and Image Processing in C++
* Photo-Based 3D Graphics in C++: Compositing, Warping, Morphing, and Other Digital Special Effects
* PIKS Foundation C Programmer's Guide
* Practical Algorithms for Image Analysis: Description, Examples, and Code
* Practical Image Processing in C
* Principles of Digital Image Processing: Core Algorithms
* Principles of Digital Image Processing: Fundamental Techniques
* VIPS: A Digital Image Processing Algorithm Development Environment
69 for Code, Image Processing

Code, Image Processing, C * *FastCV
* *OpenCV
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Data Structures for Image Processing in C
* High Performance Computer Imaging
* Numerical Recipes in C: The Art of Scientific Computing
* PIKS Foundation C Programmer's Guide
* Practical Computer Vision Using C
* Practical Image Processing in C
* Signal Processing Algorithms in Fortran and C
11 for Code, Image Processing, C

Code, Image Processing, C++ * *C++ Template Image Processing Library
* *Generic Programming for Computer Vision: The VIGRA Computer Vision Library
* *Image Processing Library 98
* *ImageLib: An Image Processing C++ Class Library
* *LibCVD: computer vision library
* *LTI-Lib
* *Mimas
* *Mobile Robot Programming Toolkit, The
* *QCV
* *Recognition And Vision Library
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Concise Introduction to Image Processing using C++, A
* Pattern Recognition and Image Processing in C++
* Photo-Based 3D Graphics in C++: Compositing, Warping, Morphing, and Other Digital Special Effects
15 for Code, Image Processing, C++

Code, Image Processing, Java * *Fiji Image Processing Package
* *HIPR2: Free WWW-based Image Processing Teaching Materials with JAVA
* *ImageJ-Plugins -- Various Plugins for the image manipulation software ImageJ
* *ImageJ: Image Processing and Analysis in Java
* *NeatVision
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Building Imaging Applications with Java(TM)
* Digital Image Processing: A Practical Introduction Using Java
* Digital Image Processing: An Algorithmic Approach Using Java
* Image Processing in Java
* Machine Vision Algorithms in Java: Techniques and Implementation
* Principles of Digital Image Processing: Core Algorithms
* Principles of Digital Image Processing: Fundamental Techniques
14 for Code, Image Processing, Java

Code, Image Processing, Matlab Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Applied Medical Image Processing: A Basic Course
* Circular and Linear Regression: Fitting Circles and Lines by Least Squares
* Digital Image Processing Using MATLAB(R), 2nd Edition
* Digital Image Processing: An Algorithmic Approach with MATLAB
* Digital Signal and Image Processing Using MATLAB(R)
* Fundamentals of Digital Image Processing: A Practical Approach with Examples in Matlab
* Fuzzy Image Processing and Applications with MATLAB
* Image Processing with MATLAB: Applications in Medicine and Biology
* Image Processing, Analysis and and Machine Vision: A MATLAB Companion
* Signal Processing Algorithms in MATLAB
13 for Code, Image Processing, Matlab

Code, Image Processing, Octave Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Applied Medical Image Processing: A Basic Course

Code, Image Pyramids * *Zoom It, Seadragon
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)

Code, Image Recognition Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Funnel Activation for Visual Recognition

Code, Image Registration Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Automatic Homographic Registration of a Pair of Images, with A Contrario Elimination of Outliers

Code, Image Restoration Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* CFSNet: Toward a Controllable Feature Space for Image Restoration
* ERL-Net: Entangled Representation Learning for Single Image De-Raining

Code, Image Retrieval Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Efficient Large-scale Image Search With a Vocabulary Tree
* Evaluating Image Retrieval
* Learning With Average Precision: Training Image Retrieval With a Listwise Loss

Code, Image Retrieval, C++ Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Efficient Large-scale Image Search With a Vocabulary Tree

Code, Image Search Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Spatial-Content Image Search in Complex Scenes

Code, Image Stitching * *Panorama Tools
* *XuvTools: eXtend yoUr View Toolkit
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)

Code, Image Synthesis Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* High-fidelity Synthesis with Disentangled Representation
* Image Synthesis From Reconfigurable Layout and Style
* OASIS: Only Adversarial Supervision for Semantic Image Synthesis

Code, Impulse Noise Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* PARIGI: a Patch-based Approach to Remove Impulse-Gaussian Noise from Images

Code, Indoor Model Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
* Floor-SP: Inverse CAD for Floorplans by Sequential Room-Wise Shortest Path

Code, Inpainting * *restoreInpaint
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
* Algorithm for Gaussian Texture Inpainting, An
* Coherent Semantic Attention for Image Inpainting
* Combined First and Second Order Total Variation Inpainting using Split Bregman
* Free-Form Image Inpainting With Gated Convolution
* Image Inpainting With Learnable Bidirectional Attention Maps
* Progressive Reconstruction of Visual Structure for Image Inpainting
* Recurrent Temporal Aggregation Framework for Deep Video Inpainting
* Total Variation Inpainting Using Split Bregman
* Variational Framework for Non-Local Inpainting
* Vision-Infused Deep Audio Inpainting
13 for Code, Inpainting

Code, InSAR Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* LiCSBAS: An Open-Source InSAR Time Series Analysis Package Integrated with the LiCSAR Automated Sentinel-1 InSAR Processor

Code, Interactive Segmentation Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Specifying Object Attributes and Relations in Interactive Scene Generation

Code, Interest Pointe Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* USIP: Unsupervised Stable Interest Point Detection From 3D Point Clouds

Code, Interest Points Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Matching Features without Descriptors: Implicitly Matched Interest Points
* SIPs: Succinct Interest Points from Unsupervised Inlierness Probability Learning

Code, Interpolation Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Reversibility Error of Image Interpolation Methods: Definition and Improvements

Code, Iris Recognition Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Iris Biometrics: From Segmentation to Template Security
* OSIRIS: An open source iris recognition software

Code, Isocontour Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Probability Density Estimation Using Isocontours and Isosurfaces: Applications to Information-Theoretic Image Registration

Code, JPEG Analysis Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* ZERO: a Local JPEG Grid Origin Detector Based on the Number of DCT Zeros and its Applications in Image Forensics

Code, JPEG Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Reliable JPEG Quantization Table Estimator, A

Code, Kalman Filter * *Kalman Filter Library
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Introduction to the Kalman Filter, An

Code, Kernel Expansion * *McKernel: A Library for Approximate Kernel Expansions in Log-linear Time
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Code, Landmarks Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Precision Landmark Location for Machine Vision and Photogrammetry: Finding and Achieving the Maximum Possible Accuracy
* Unsupervised Learning of Landmarks by Descriptor Vector Exchange

Code, Lane Detection Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
* Unsupervised Labeled Lane Markers Using Maps

Code, Layout Extimation Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
* Single-shot cuboids: Geodesics-based end-to-end Manhattan aligned layout estimation from spherical panoramas

Code, Learning * *Torch: Machine-Learning Library
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Bidirectional One-Shot Unsupervised Domain Mapping
* Boosting Few-Shot Visual Learning With Self-Supervision
* Creativity Inspired Zero-Shot Learning
* Cross-X Learning for Fine-Grained Visual Categorization
* Deep Metric Transfer for Label Propagation with Limited Annotated Data
* Delving into Inter-Image Invariance for Unsupervised Visual Representations
* Meta R-CNN: Towards General Solver for Instance-Level Low-Shot Learning
* OSCAR: Object-Semantics Aligned Pre-Training for Vision-Language Tasks
* S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration
* Scaling and Benchmarking Self-Supervised Visual Representation Learning
* Semi-Supervised Learning by Augmented Distribution Alignment
* Symmetry and Group in Attribute-Object Compositions
* Unsupervised Pre-Training of Image Features on Non-Curated Data
18 for Code, Learning

Code, Least Squares Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Analysis of Sketched IRLS for Accelerated Sparse Residual Regression, An

Code, Lens Distortion Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Algebraic Lens Distortion Model Estimation
* Iterative Optimization Algorithm for Lens Distortion Correction Using Two-Parameter Models, An

Code, Level Set Segmentation Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Level Set Curve Evolution Partitioning of Polarimetric Images
* Variational and Level Set Methods in Image Segmentation

Code, Levenberg-Marquardt Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Algorithm for Least-Squares Estimation of Nonlinear Parameters, An
* Levenberg-Marquardt nonlinear least squares algorithms in C/C++

Code, LIDAR Processing Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* waveformlidar: An R Package for Waveform LiDAR Processing and Analysis

Code, LIDAR Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Gated2Depth: Real-Time Dense Lidar From Gated Images

Code, Line Detection Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Iterative Hough Transform for Line Detection in 3D Point Clouds

Code, Line Segments Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Gestaltic Grouping of Line Segments
* LSD: a Line Segment Detector

Code, Localization Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* IM2GPS: estimating geographic information from a single image
* Prior Guided Dropout for Robust Visual Localization in Dynamic Environments
* Stochastic Attraction-Repulsion Embedding for Large Scale Image Localization

Code, Mammography Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Efficient presentation of DICOM mammography images using Matlab

Code, Matching Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Exploring Patch Similarity in an Image
* Feature Correspondence Via Graph Matching: Models and Global Optimization
* Implementation of the Self-Similarity Descriptor
* LIBPMK: A Pyramid Match Toolkit
* Local Region Expansion: A Method for Analyzing and Refining Image Matches
* Matching of Weakly-Localized Features under Different Geometric Models
* Modal Matching for Correspondence and Recognition
* Probabilistic Model Distillation for Semantic Correspondence
* Semantic Part Detection via Matching: Learning to Generalize to Novel Viewpoints From Limited Training Data
* Software Library for Appearance Matching (SLAM)
13 for Code, Matching

Code, Mathematical Software * *NIST Guide to Available Mathematical Software

Code, Matlab Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Robust Jointly Sparse Regression with Generalized Orthogonal Learning for Image Feature Selection

Code, Matting Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Indices Matter: Learning to Index for Deep Image Matting

Code, Mean Shift Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Implementation of the Mean Shift Algorithm, An

Code, Medical Analysis * *Stain Normalization toolbox for histopathology image analysis
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Code, Medical Image Analysis * *Insight Segmentation and Registration Toolkit (ITK)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)

Code, Mesh Compression Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Progressive Compression of Triangle Meshes

Code, Mesh Generation Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Implementation and Parallelization of the Scale Space Meshing Algorithm, An

Code, Mesh Models * *VolMorph Documentation
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* ply2vri
* Zippered Polygon Meshes from Range Images

Code, Mesh Pose Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Neural Pose Transfer by Spatially Adaptive Instance Normalization

Code, Mesh Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* TexturePose: Supervising Human Mesh Estimation With Texture Consistency

Code, Metric Learning Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Collect and Select: Semantic Alignment Metric Learning for Few-Shot Learning
* MIC: Mining Interclass Characteristics for Improved Metric Learning

Code, MGLM Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Multivariate General Linear Models (MGLM) on Riemannian Manifolds with Applications to Statistical Analysis of Diffusion Weighted Images

Code, Model Compression Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Learning Accurate Performance Predictors for Ultrafast Automated Model Compression

Code, Modes Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Mode-Finding for Mixtures of Gaussian Distributions

Code, Moments Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Moment Matching for Multi-Source Domain Adaptation

Code, Monocular Depth * *Recurrent Asynchronous Multimodal Networks + Events, Frames, Semantic labels, and Depth maps recorded in CARLA simulator
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)

Code, Morphology * *Mathematical Morphology
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Adaptive Anisotropic Morphological Filtering Based on Co-Circularity of Local Orientations

Code, Mosaic * *Photosynth
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Scene Collages and Flexible Camera Arrays

Code, Motion Blur * 3-D Shape Estimation and Image Restoration: Exploiting Defocus and Motion-Blur
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* E-CIR: Event-Enhanced Continuous Intensity Recovery

Code, Motion Capture * *CMU Graphics Lab Motion Capture Database
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)

Code, Motion Segmentation Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Implementation of Bilayer Segmentation of Live Video
* Motion Segmentation in the Presence of Outlying, Incomplete, or Corrupted Trajectories

Code, Motion Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Compositional Video Prediction
* Learning to Estimate Hidden Motions with Global Motion Aggregation
* Linear Algorithm for Motion from Three Weak Perspective Images Using Euler Angles

Code, MR Reconstruction * *Synergistic Image Reconstruction Framework SIRF
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Code, Mumford-Shah Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* PALMS Image Partitioning: A New Parallel Algorithm for the Piecewise Affine-Linear Mumford-Shah Model

Code, Music Processing Section: OCR, Document Analysis and Character Recognition Systems (H)
* Staff Line Removal Toolkit for Gamera

Code, Network Pruning Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Resolution Switchable Networks for Runtime Efficient Image Recognition

Code, Neural Netowrks Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* HM-NAS: Efficient Neural Architecture Search via Hierarchical Masking
* PR Product: A Substitute for Inner Product in Neural Networks

Code, Neural Nets Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* WeightNet: Revisiting the Design Space of Weight Networks

Code, Neural Networks * *Deep Learning Tool Kit for Medical Imaging
* *McKernel: A Library for Approximate Kernel Expansions in Log-linear Time
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Bit-Flip Attack: Crushing Neural Network With Progressive Bit Search
* Decision explanation and feature importance for invertible networks
* Enhanced neural gas network for prototype-based clustering
* GhostNets on Heterogeneous Devices via Cheap Operations
* gvnn: Neural Network Library for Geometric Computer Vision
* MetaPruning: Meta Learning for Automatic Neural Network Channel Pruning
* Multinomial Distribution Learning for Effective Neural Architecture Search
* Overcoming Catastrophic Forgetting With Unlabeled Data in the Wild
* Pattern Recognition with Neural Networks in C++
* Universally Slimmable Networks and Improved Training Techniques
13 for Code, Neural Networks

Code, Noise Estimation Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Analysis and Extension of the Ponomarenko et al. Method, Estimating a Noise Curve from a Single Image

Code, Noise Removal Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Analysis and Implementation of the FFDNet Image Denoising Method, An
* EPLL: An Image Denoising Method Using a Gaussian Mixture Model Learned on a Large Set of Patches

Code, Normalization Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity

Code, Numerical Algorithms Section: Books, Collections, Overviews, General, and Surveys (H)
* Numerical Recipes in C: The Art of Scientific Computing

Code, Object Detection * 100 lines of code for shape-based object localization
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* CenterNet: Keypoint Triplets for Object Detection
* Delving Into Robust Object Detection From Unmanned Aerial Vehicles: A Deep Nuisance Disentanglement Approach
* Development of Fast Refinement Detectors on AI Edge Platforms
* Double Head Predictor based Few-Shot Object Detection for Aerial Imagery
* Dynamic Head: Unifying Object Detection Heads with Attentions
* EGNet: Edge Guidance Network for Salient Object Detection
* Enriched Feature Guided Refinement Network for Object Detection
* Explore Spatio-Temporal Aggregation for Insubstantial Object Detection: Benchmark Dataset and Baseline
* FCOS: Fully Convolutional One-Stage Object Detection
* Integral Object Mining via Online Attention Accumulation
* Investigating Attention Mechanism in 3D Point Cloud Object Detection
* Learning Rich Features at High-Speed for Single-Shot Object Detection
* Monocular 3D Object Detection with Pseudo-LiDAR Point Cloud
* Multiview Detection with Feature Perspective Transformation
* OTA: Optimal Transport Assignment for Object Detection
* Progressive End-to-End Object Detection in Crowded Scenes
* RepPoints: Point Set Representation for Object Detection
* Scale-Aware Trident Networks for Object Detection
* SCRDet: Towards More Robust Detection for Small, Cluttered and Rotated Objects
* Single-Domain Generalized Object Detection in Urban Scene via Cyclic-Disentangled Self-Distillation
* Stacked Cross Refinement Network for Edge-Aware Salient Object Detection
* TKD: Temporal Knowledge Distillation for Active Perception
* Towards Interpretable Object Detection by Unfolding Latent Structures
* UAVision: A Modular Time-Constrained Vision Library for Color-Coded Object Detection
32 for Code, Object Detection

Code, Object Recognition Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Spatial Priors for Part-Based Recognition Using Statistical Models
* Weakly Supervised Learning of Part-Based Spatial Models for Visual Object Recognition

Code, OCR * *GOCR
* *Google Tesseract-OCR
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Nist Form-Based Handprint Recognition System (Release 2.2)

Code, Odometry Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Optical Flow Field Computations and Use (H)
* Data-Efficient Collaborative Decentralized Thermal-Inertial Odometry
* Event-aided Direct Sparse Odometry
* VIMO: Simultaneous Visual Inertial Model-based Odometry and Force Estimation

Code, Omnidirectional Images Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Toolbox and dataset for the development of saliency and scanpath models for omnidirectional/360° still images

Code, Open Source * *AAM Building
* *C++ Template Image Processing Library
* *LTI-Lib
* *Mimas
* *OpenCV
* *OpenVidia
* *OSGeo: Open Source Geospatial Foundation
* *VXL
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
11 for Code, Open Source

Code, Optic Flow * *Gain-Adaptive KLT Tracking and TV-L1 optical flow on the GPU
* *Optic Flow Evaluation
Section: Optical Flow Field Computations and Use (H)
* Performance of Optical Flow Techniques
* Real-Time Quantized Optical Flow
* Robust Estimation of Multiple Motions: Parametric and Piecewise-Smooth Flow-Fields, The

Code, Optical Flow Section: Optical Flow Field Computations and Use (H)
* Analysis and Speedup of the FALDOI Method for Optical Flow Estimation, An
* Comparison of Optical Flow Methods under Stereomatching with Short Baselines
* E-RAFT: Dense Optical Flow from Event Cameras
* Horn-Schunck Optical Flow with a Multi-Scale Strategy
* Implementation of Combined Local-Global Optical Flow, An
* Inverse Compositional Algorithm for Parametric Registration, The
* Joint TV-L1 Optical Flow and Occlusion Estimation
* Line Search Multilevel Truncated Newton Algorithm for Computing the Optical Flow, A
* On Anisotropic Optical Flow Inpainting Algorithms
* Robust Discontinuity Preserving Optical Flow Methods
* Robust Optical Flow Estimation
* TV-L1 Optical Flow Estimation
13 for Code, Optical Flow

Code, Optimization Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Librjmcmc: An Open-source Generic C++ Library For Stochastic Optimization
* Sparse Non-linear Least Squares Optimization for Geometric Vision

Code, Optimization, C++ * *Ceres Solver
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)

Code, Otsu Segmentation Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* C++ Implementation of Otsu's Image Segmentation Method, A

Code, Pansharpening Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Implementation of Nonlocal Pansharpening Image Fusion

Code, Pattern Recognition * *MultiSpec: A Freeware Multispectral Image Data Analysis System
* *Presto-Box: Pattern REcognition Scilab TOolBOX
* *PRTools: The Matlab Toolbox for Pattern Recognition
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Code, PCA Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Framework for Robust Subspace Learning, A

Code, Pedestrian Detection Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Mask-Guided Attention Network for Occluded Pedestrian Detection

Code, Perceptual Grouping Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Computing Perceptual Organization in Computer Vision
* in-depth study of graph partitioning measures for perceptual organization, An

Code, PET Reconstruction * *Synergistic Image Reconstruction Framework SIRF
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Code, Phase Retrieval Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Robust Phase Retrieval with the Swept Approximate Message Passing (prSAMP) Algorithm

Code, Phase Unwrapping Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Phase Unwrapping using a Joint CNN and SQD-LSTM Network

Code, Plant Phenotype Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* EasyIDP: A Python Package for Intermediate Data Processing in UAV-Based Plant Phenotyping

Code, Point Alignment Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Contrario 3D Point Alignment Detection Algorithm, A

Code, Point Cloud Convolutions Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds

Code, Point Cloud Registration * *TEASER++: Certifiable 3D Registration
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)

Code, Point Cloud Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Progressive Point Cloud Deconvolution Generation Network
* Quantitative Comparison of Point Cloud Compression Algorithms With PCC Arena

Code, Point Spread Function Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Recovering the Subpixel PSF from Two Photographs at Different Distances

Code, Poisson Solver Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Analysis and Implementation of Multigrid Poisson Solvers With Verified Linear Complexity, An

Code, Poisson Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Poisson Image Editing

Code, Pose Calibration Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Orthographic Projection Model for Pose Calibration of Long Focal Images, The

Code, Pose Estimation Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* CullNet: Calibrated and Pose Aware Confidence Scores for Object Pose Estimation
* Motion Guided 3d Pose Estimation from Videos
* On Evaluation of 6D Object Pose Estimation
* Unsupervised Shape and Pose Disentanglement for 3d Meshes

Code, Pose Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* MarkerPose: Robust Real-time Planar Target Tracking for Accurate Stereo Pose Estimation

Code, Posture Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Local Assessment of Statokinesigram Dynamics in Time: An in-Depth Look at the Scoring Algorithm

Code, Pretraining Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* How Useful Is Self-Supervised Pretraining for Visual Tasks?

Code, PSF Estimation Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Non-parametric sub-pixel local point spread function estimation

Code, Python Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Analysis and Implementation of the HDR+ Burst Denoising Method, An

Code, Query Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Improving One-Stage Visual Grounding by Recursive Sub-query Construction

Code, Radar * *Radar Tools
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)

Code, Radiometric Calibration Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Radiometric Self Calibration

Code, Random Forest Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Confidence intervals for the random forest generalization error

Code, Range Registration * *VripPack: Volumetric Range Image Processing Package
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)

Code, RANSAC Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Automatic RANSAC by Likelihood Maximization

Code, Raw Data Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Image Unprocessing: A Pipeline to Recover Raw Data from sRGB Images

Code, RBF Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* RBF-Softmax: Learning Deep Representative Prototypes with Radial Basis Function Softmax

Code, Re-Identification Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Beyond Human Parts: Dual Part-Aligned Representations for Person Re-Identification
* Dual-Path Model With Adaptive Attention for Vehicle Re-Identification, A
* Mixed High-Order Attention Network for Person Re-Identification
* MVP Matching: A Maximum-Value Perfect Matching for Mining Hard Samples, With Application to Person Re-Identification
* Omni-Scale Feature Learning for Person Re-Identification
* Robust Person Re-Identification by Modelling Feature Uncertainty
* Robust Re-identification by Multiple Views Knowledge Distillation
* Self-Similarity Grouping: A Simple Unsupervised Cross Domain Adaptation Approach for Person Re-Identification
* Spectral Feature Transformation for Person Re-Identification
11 for Code, Re-Identification

Code, Recognition Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Attention Pyramid Module for Scene Recognition
* Hybrid Approach to Tiger Re-Identification, A
* Part-Pose Guided Amur Tiger Re-Identification
* Pose-Guided Complementary Features Learning for Amur Tiger Re-Identification
* Strong Baseline for Tiger Re-ID and its Bag of Tricks, A
7 for Code, Recognition

Code, Rectification Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Quasi-Euclidean Epipolar Rectification
* Rectification for any epipolar geometry

Code, Recurrent Networks * *Recurrent Asynchronous Multimodal Networks + Events, Frames, Semantic labels, and Depth maps recorded in CARLA simulator
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)

Code, Region Matching Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Affine Invariant Patch Similarity, An

Code, Registration Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* AROSICS: An Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Data
* elastix: A Toolbox for Intensity-Based Medical Image Registration
* Few-Shot Unsupervised Image-to-Image Translation
* Improvements of the Inverse Compositional Algorithm for Parametric Motion Estimation
* Iterative Image Registration Technique with an Application to Stereo Vision, An
8 for Code, Registration

Code, Regularization Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Delving Deep Into Label Smoothing
* Isotonic Modeling with Non-Differentiable Loss Functions with Application to Lasso Regularization

Code, Relations Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Heterogeneous Representation Learning and Matching for Few-Shot Relation Prediction
* Visual Relation Grounding in Videos

Code, Relighting Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Deep Single-Image Portrait Relighting
* Lighting Sensitive Display

Code, Rendering Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Accelerating Monte Carlo Renderers by Ray Histogram Fusion
* Soft Rasterizer: A Differentiable Renderer for Image-Based 3D Reasoning

Code, Representation Learning Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* On the Integration of Self-Attention and Convolution

Code, Restoration * *restoreInpaint
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)

Code, Retinex Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Center/Surround Retinex: Analysis and Implementation
* Multiscale Retinex
* Retinex in Matlab
* Retinex Poisson Equation: a Model for Color Perception
* Screened Poisson Equation for Image Contrast Enhancement

Code, Retinex, Matlab Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Retinex in Matlab

Code, Retrieval Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Adaptive Offline Quintuplet Loss for Image-text Matching

Code, RGB-D * *Hydra:
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)

Code, Robust Fitting Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Deterministic Approximate Methods for Maximum Consensus Robust Fitting

Code, Saliency Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Deep Learning for Light Field Saliency Detection
* Generation and Detection of Alignments in Gabor Patterns
* PointCloud Saliency Maps
* SaltiNet: Scan-Path Prediction on 360 Degree Images Using Saliency Volumes
7 for Code, Saliency

Code, SAR Filters Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Non-Local Means Filters for Full Polarimetric Synthetic Aperture Radar Images with Stochastic Distances

Code, SAR Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Inverse Synthetic Aperture Radar Imaging With MATLAB Algorithms

Code, SAR, Matlab Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Inverse Synthetic Aperture Radar Imaging With MATLAB Algorithms

Code, Scale Space Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Finite Difference Schemes for MCM and AMSS

Code, Scene Flow Section: Optical Flow Field Computations and Use (H)
* Learning Scene Dynamics from Point Cloud Sequences

Code, Scene Graph * *Hydra:
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)

Code, Search Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Consensus Maximization Tree Search Revisited
* Progressive Differentiable Architecture Search: Bridging the Depth Gap Between Search and Evaluation

Code, Segmenation Evaluation Section: Books, Collections, Overviews, General, and Surveys (H)
* Automated Performance Evaluation of Range Image Segmentation

Code, Segmentation * *Edison: Edge Detection and Image SegmentatiON system
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* AdaptIS: Adaptive Instance Selection Network
* Adaptive Early-Learning Correction for Segmentation from Noisy Annotations
* AMP: Adaptive Masked Proxies for Few-Shot Segmentation
* Asymmetric Non-Local Neural Networks for Semantic Segmentation
* Automatic 1D Histogram Segmentation and Application to the Computation of Color Palettes
* Bayesian Adaptive Superpixel Segmentation
* Berkeley Segmentation Dataset and Benchmark, The
* C++ Implementation of Otsu's Image Segmentation Method, A
* CCNet: Criss-Cross Attention for Semantic Segmentation
* Code: Active Segmentation With Fixation
* Confidence Regularized Self-Training
* Consistency-Regularized Region-Growing Network for Semantic Segmentation of Urban Scenes With Point-Level Annotations
* Contrastive and Selective Hidden Embeddings for Medical Image Segmentation
* Crossover-Net: Leveraging vertical-horizontal crossover relation for robust medical image segmentation
* Disentangled Non-local Neural Networks
* Dynamic Threshold Determination by Local and Global Edge Evaluation
* Efficient Graph-Based Image Segmentation
* Experimental Comparison of Min-Cut/Max-Flow Algorithms for Energy Minimization in Vision, An
* Graph Partitioning Active Contours (GPAC) for Image Segmentation
* InstaBoost: Boosting Instance Segmentation via Probability Map Guided Copy-Pasting
* Intellegent Scissors: Interactive tool for image segmentation
* Interactive Segmentation Based on Component-trees
* Layered Embeddings for Amodal Instance Segmentation
* Level-set image segmenation software
* Matlab toolbox for Level Set Methods
* Normalized cut image segmenation software
* Ratio Contour Code
* Robust Analysis of Feature Spaces: Color Image Segmentation
* Segmentation skin cancer images
* Segmentation with Active Contours
* Semantic-Oriented Labeled-to-Unlabeled Distribution Translation for Image Segmentation
* ShapeMask: Learning to Segment Novel Objects by Refining Shape Priors
* ShelfNet for Fast Semantic Segmentation
* SOLO: Segmenting Objects by Locations
* Strip Pooling: Rethinking Spatial Pooling for Scene Parsing
* Watervoxels
41 for Code, Segmentation

Code, Segmentation, C Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Normalized cut image segmenation software

Code, Segmentation, C++ Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* C++ Implementation of Otsu's Image Segmentation Method, A
* Robust Analysis of Feature Spaces: Color Image Segmentation

Code, Segmentation, Matlab Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Matlab toolbox for Level Set Methods

Code, Semantic Segmentation Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Event-based Asynchronous Sparse Convolutional Networks
* Semantic Segmentation: A Zoology of Deep Architectures
* Study of RobustNet, a Domain Generalization Method for Semantic Segmentation, A

Code, Shape from Shading Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Integration of Shape from Shading and Stereo
* Shape From Shading Using Linear-Approximation
* Shape from Shading: A Survey

Code, SIFT * *SIFT Feature Detector
* *VLFeat
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* ASIFT: An Algorithm for Fully Affine Invariant Comparison
* Distinctive Image Features from Scale-Invariant Keypoints

Code, Signal Processing * *IT++ Mathematical, Signal Processing and Communication Routines
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Signal Processing Algorithms in Fortran and C
* Signal Processing Algorithms in MATLAB

Code, Signal Processing, C++ * *IT++ Mathematical, Signal Processing and Communication Routines
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)

Code, Skeleton Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Finding the Skeleton of 2D Shape and Contours: Implementation of Hamilton-Jacobi Skeleton

Code, Skin Spots * *APP for Monitoring Skin Spots
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Code, SLAM * *Kimera
* *Ultimate SLAM
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Continuous-Time vs. Discrete-Time Vision-based SLAM: A Comparative Study
* SLAMANTIC: Leveraging Semantics to Improve VSLAM in Dynamic Environments
* tinySLAM: A SLAM algorithm in less than 200 lines C-language program

Code, SLIC Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Bilateral K-Means for Superpixel Computation (the SLIC Method)

Code, Snakes * *Mega Wave
* *qsnake_demo
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Code: Active Segmentation With Fixation
* Gradient Vector Flow: A New External Force for Snakes
* Real Time Morphological Snakes Algorithm, A
7 for Code, Snakes

Code, Space Envelope Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Space Envelope: A Representation for 3D Scenes, The

Code, Spectal Bias Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* On Measuring and Controlling the Spectral Bias of the Deep Image Prior

Code, Spectral Clustering Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* CAEclust: A Consensus of Autoencoders Representations for Clustering

Code, Splines Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Theory and Practice of Image B-Spline Interpolation

Code, Stabilization Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Mao-Gilles Stabilization Algorithm

Code, Steerable Filter Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Steerable Pyramid: A Flexible Architecture for Multi-Scale Derivative Computation, The

Code, Stereo Matching Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Bilaterally Weighted Patches for Disparity Map Computation
* Deep Material-Aware Cross-Spectral Stereo Matching
* Fast Cost-Volume Filtering for Visual Correspondence and Beyond
* Kolmogorov and Zabih's Graph Cuts Stereo Matching Algorithm
* Stereo Disparity through Cost Aggregation with Guided Filter

Code, Stereo * *MSRC Stereo Vision C# SDK, The
* *Real Time Dense Stereo
* *SRI Stereo Engine
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* ChiTransformer: Towards Reliable Stereo from Cues
* Computing Visual Correspondence with Occlusions via Graph Cuts
* Disparity Estimation Networks for Aerial and High-Resolution Satellite Images: A Review
* Efficient Belief Propagation for Early Vision
* On the Over-Smoothing Problem of CNN Based Disparity Estimation
* Point-Based Multi-View Stereo Network
* Polar Epipolar Rectification, The
* Shape and the Stereo Correspondence Problem
* Stereo Matching With Nonlinear Diffusion
* Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms, A
15 for Code, Stereo

Code, STIP Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Evaluation of local spatio-temporal features for action recognition

Code, Structure from Motion Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Automatic Non-rigid 3D Modeling from Video
* Bundler: Structure from Motion for Unordered Image Collections

Code, Structured Light * *Kinect-Like 3D camera
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)

Code, Style Transfer Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Photorealistic Style Transfer via Wavelet Transforms

Code, Super-Resolution * *Super-Resolution Code
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Super-Resolution Imaging

Code, Super Resolution Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Implementing Handheld Burst Super-Resolution
* Lightweight and Accurate Recursive Fractal Network for Image Super-Resolution
* Robust Temporal Super-Resolution for Dynamic Motion Videos
* Single image super-resolution from transformed self-exemplars

Code, Superpixel Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Bilateral K-Means for Superpixel Computation (the SLIC Method)

Code, Superresolution Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Constrained and Unconstrained Inverse Potts Modelling for Joint Image Super-Resolution and Segmentation

Code, Support Vector Machines * *LIBSVMTL: a Support Vector Machine Template Library
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* LIBSVM: a library for support vector machines

Code, SURF Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Analysis of the SURF Method, An

Code, Surface Appearance Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Time-varying Surface Appearance: Acquisition, Modeling, and Rendering

Code, Surface Fitting Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Linear Fitting with Missing Data for Structure-from-Motion

Code, Surfaces, Matlab Section: Books, Collections, Overviews, General, and Surveys (H)
* Modeling of Curves and Surfaces with MATLAB®

Code, Surgery Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* IGSTK: an open source software toolkit for image-guided surgery

Code, SVD Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* SVD: A Large-Scale Short Video Dataset for Near-Duplicate Video Retrieval

Code, Swin Transform * *Swin-Transformer-Object-Detection
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)

Code, Symmetry Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Gradient Product Transform: An Image Filter for Symmetry Detection, The
* Learning to Reconstruct Symmetric Shapes using Planar Parameterization of 3D Surface

Code, Target Detection Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
* Portability Study of an OpenCL Algorithm for Automatic Target Detection in Hyperspectral Images

Code, Tensor Algebra Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Spherical Tensor Algebra: A Toolkit for 3D Image Processing

Code, Terrain Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Modeling Extent-of-Texture Information for Ground Terrain Recognition

Code, Text Detection Section: OCR, Document Analysis and Character Recognition Systems (H)
* State-of-the-Art in Action: Unconstrained Text Detection

Code, Texture Analysis Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* JAVA-based Texture Analysis Employing Neighborhood Gray-Tone Difference Matrix (NGTDM) for Optimization of Land Use Classifications in High Resolution Remote Sensing Data

Code, Texture Analysis, Java Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* JAVA-based Texture Analysis Employing Neighborhood Gray-Tone Difference Matrix (NGTDM) for Optimization of Land Use Classifications in High Resolution Remote Sensing Data

Code, Texture Synthesis Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Efros and Freeman Image Quilting Algorithm for Texture Synthesis
* Micro-Texture Synthesis by Phase Randomization

Code, Texture Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Cartoon+Texture Image Decomposition

Code, TIFF * *LibTIFF: TIFF Library and Utilities
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)

Code, Time Series Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
* Association Rules Discovery of Deviant Events in Multivariate Time Series: An Analysis and Implementation of the SAX-ARM Algorithm

Code, Time Warping Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Generalized Canonical Time Warping

Code, Total Variation Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Chambolle's Projection Algorithm for Total Variation Denoising
* Rudin-Osher-Fatemi Total Variation Denoising using Split Bregman
* Total Variation Deconvolution Using Split Bregman

Code, Tracking Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* DeepTAM: Deep Tracking and Mapping with Convolutional Neural Networks
* Design and Implementation of People Tracking Algorithms for Visual Surveillance Applications
* Fast Visual Object Tracking using Ellipse Fitting for Rotated Bounding Boxes
* Fragments Tracker
* GPU_KLT: A GPU-based Implementation of the Kanade-Lucas-Tomasi Feature Tracker
* KLT: An Implementation of the Kanade-Lucas-Tomasi Feature Tracker
* Learning Discriminative Model Prediction for Tracking
* Learning the Statistics of People in Images and Video
* Lucas-Kanade 20 Years On
* MITT: Medical Image Tracking Toolbox
* Robust Multi-Modality Multi-Object Tracking
* Skimming-Perusal Tracking: A Framework for Real-Time and Robust Long-Term Tracking
* STEm-Seg: Spatio-temporal Embeddings for Instance Segmentation in Videos
* Tracker Fusion for Robustness in Visual Feature Tracking
* Tracking by an Optimal Sequence of Linear Predictors
* Tracking Vector Magnetograms with the Magnetic Induction Equation
22 for Code, Tracking

Code, Training Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Activate or Not: Learning Customized Activation
* t-vMF Similarity For Regularizing Intra-Class Feature Distribution

Code, Tranformations Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Highly-Expressive Spaces of Well-Behaved Transformations: Keeping it Simple

Code, Tree Bark Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* CNN-based Method for Segmenting Tree Bark Surface Singularites

Code, Turbulence Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Implementation of the Centroid Method for the Correction of Turbulence
* Study of the Principal Component Analysis Method for the Correction of Images Degraded by Turbulence

Code, UAV Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* SlimYOLOv3: Narrower, Faster and Better for Real-Time UAV Applications

Code, Vanishing Points Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Unsupervised Point Alignment Detection Algorithm, An
* Vanishing Point Detection in Urban Scenes Using Point Alignments

Code, Vascular tree * *Vascular Modeling Toolkit, The
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* OpenCCO: An Implementation of Constrained Constructive Optimization for Generating 2D and 3D Vascular Trees

Code, Vectorization Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Binary Shape Vectorization by Affine Scale-space

Code, Vehicle Detection Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Connecting Language and Vision for Natural Language-Based Vehicle Retrieval

Code, Vehicle Synthesis Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Simulating Content Consistent Vehicle Datasets with Attribute Descent

Code, Video Analysis Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* AWSD: Adaptive Weighted Spatiotemporal Distillation for Video Representation

Code, Video Deblurring Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Implementation of Local Fourier Burst Accumulation for Video Deblurring

Code, Video Denoising Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Video Denoising with Optical Flow Estimation

Code, Video Interpolation Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* PoSNet: 4x Video Frame Interpolation Using Position-Specific Flow

Code, Video Noise Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Signal-dependent Video Noise Estimator Via Inter-frame Signal Suppression, A

Code, Video Object Segmentatioin Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* RANet: Ranking Attention Network for Fast Video Object Segmentation

Code, Video Processing * *Rad Video Tools
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Efficient 3D Video Engine Using Frame Redundancy
* Practical Image and Video Processing Using MATLAB
* SlowFast Networks for Video Recognition
7 for Code, Video Processing

Code, Video Processing, Matlab Section: Books, Collections, Overviews, General, and Surveys (H)
* Practical Image and Video Processing Using MATLAB

Code, Video Recognition Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Video Transformer Network

Code, Video Segmentation Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule Routing

Code, Video Understanding Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Graph-Based Framework to Bridge Movies and Synopses, A
* TSM: Temporal Shift Module for Efficient Video Understanding

Code, Viedo Denoise Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Implementation of VBM3D and Some Variants

Code, View Syntheses Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Pose-Based View Synthesis for Vehicles: A Perspective Aware Method

Code, Viewing * *Lotus Hill Institute

Code, Virtual Reality Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* UnrealCV: Connecting Computer Vision to Unreal Engine

Code, Vision Transformer Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* CvT: Introducing Convolutions to Vision Transformers

Code, Visual Effects Section: Books, Collections, Overviews, General, and Surveys (H)
* Computer Vision for Visual Effects

Code, Visual Learning Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Visual Understanding via Multi-Feature Shared Learning With Global Consistency

Code, Visual Odometry * *SVO Pro: Semi-direct Visual-Inertial Odometry and SLAM for Monocular, Stereo, and Wide Angle Cameras
Section: Optical Flow Field Computations and Use (H)

Code, Visual Q-A Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Why Does a Visual Question Have Different Answers?

Code, Visual Worlds Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Transferable Visual Words: Exploiting the Semantics of Anatomical Patterns for Self-Supervised Learning

Code, Visualization * *Mathematical Morphology
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
* Language Features Matter: Effective Language Representations for Vision-Language Tasks
* Language-Agnostic Visual-Semantic Embeddings

Code, Watermark Section: OCR, Document Analysis and Character Recognition Systems (H)
* Intelligent Watermarking Techniques

Code, Watershed Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Parallel, O(n) Algorithm for an Unbiased, Thin Watershed, A

Code, Wavelets * *Mega Wave
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Wavelab

Code, Wavelets, Matlab Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Wavelab

Code, Wind Turbine Section: Optical Flow Field Computations and Use (H)
* Single Date Wind Turbine Detection on Sentinel-2 Optical Images

Code, Wireframe Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* End-to-End Wireframe Parsing

Code, X-Ray Analysis Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Cradle Removal in X-Ray Images of Panel Paintings

Coded Aperture Section: Coded Aperture Compressive Sensing (H2)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)

Coding Section: Coding -- Coding Theory, Communications, etc. (H2)
Section: Coding, Compression, Acoustic Signals, Sounds, Audio (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Section: Reconstruction from Coded Images, Error Recovery (H3)

Coffee Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Coffee Trees, Trees as Crops, Tea Trees (H4)

Cognitive Radio Section: Cognitive Radio (H3)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)

Coins Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Metal, Coins (H4)

Colinear Lines Section: Colinear Line Segments (Collinear) (H2)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Finding Picture Edges Through Collinearity of Feature Points

Collections, Early Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Early Collections of Articles (H2)

Collections, General Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Collections -- General Computer Vision (H2)

Collections, Special Topics Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Collections, Special Topics or Conferences (H2)

Collision Avoidance Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Collision Avoidance, Collision Detection, Marine Vessels, Ships (H4)
Section: Collision Avoidance, Collision Detection, Vehicles, Objects on the Road (H4)
Section: Obstacles, Objects on the Road Using Radar, Sonar, LiDAR, Active Vision (H4)

Collision Detection Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Airplane Obstacles, Collision Detection, Sense and Avoid (H3)
Section: Collision Avoidance, Collision Detection, Marine Vessels, Ships (H4)
Section: Collision Avoidance, Collision Detection, Vehicles, Objects on the Road (H4)
Section: Focus of Expansion and Other Features (H2)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Obstacle Detection, Time to Collision Techniques (H2)
Section: Obstacles, Objects on the Road Using Radar, Sonar, LiDAR, Active Vision (H4)
Section: Optical Flow Field Computations and Use (H)
Section: Railroads, Inspection, Obstacles (H3)
Section: Target Tracking, Collision Detection (H3)
Section: Translation Only (H2)
12 for Collision Detection

Collisions Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Traffic Collisions, Accidents, Analysis, Congestion, Not Image Analysis (H4)

Colonoscopy Section: Medical Applications -- Colonoscopy, Colon Cancer (H2)
Section: Medical Applications -- Colonoscopy, Polyp Detection, Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Color Calibration Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Color Calibration for Display and Printing (H3)
Section: Photometric Calibration, Radiometric Calibration, Spectral Calibration, Color Calibration (H2)

Color Clustering Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Defect Detection in Random Color Textures

Color Constancy Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Color Constancy, Recognition, Healey Papers (H3)
Section: Color Constancy, Recognition, Simon Fraser Univ. (Funt and Finlayson) Papers (H3)
Section: Color Constancy, Retinex (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Reflectance Computations, Albedo (H2)
* Illumination-Invariant Matching of Deterministic Local Structure in Color Images, The
7 for Color Constancy

Color Cooccurrence Matrix Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Color Texture Segmentation for Clothing in a Computer-Aided Fashion Design System

Color Correction Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Color Correction (H3)
Section: Color Transfer, Color Enhancement, Color Correction (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Haze, Dehazing, Color Correction (H3)
Section: Lighting Effects, View Generation, Graphics Issues (H3)
Section: Underwater Imaging, Color Correction, Restoration (H3)
7 for Color Correction

Color Histogram Matching Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Histogram Matching, Histogram Comparisons (H3)
Section: Recognition by Color Indexing (H2)

Color Image Restoration Section: Color, Multispectral, Multi-Channel Restoration (H2)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)

Color Indexing Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Recognition by Color Indexing (H2)
* Automatic Detection of Human Nudes
* Finding Waldo, or Focus of Attention Using Local Color Information
* Image Retrieval Using Fuzzy Evaluation of Color Similarity
* Query by Image and Video Content: The QBIC System
8 for Color Indexing

Color Matching Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Recognition by Color Indexing (H2)

Color Models Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Color Models, Color Representation (H2)
Section: Color Sensors, Sensor Models (H3)
Section: Color Transfer, Color Enhancement, Color Correction (H3)
Section: Computational Models of Color, Computer Based Color Models (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Reflections and Color Models, Reflectance (H3)
* Flexible Color Point Distribution Models
* Region Competition and its Analysis: A Unified Theory for Image Segmentation
9 for Color Models

Color Perception, Survey Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Survey on Color: Aspects of Perception and Computation

Color Quantization Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Color Quantization of Images (H4)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Tone Mapping of Images (H4)
* Color Texture Segmentation for Clothing in a Computer-Aided Fashion Design System

Color Segmentation Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Color Applied to Segmentation (H1)
Section: Color Segmentation, Healey (H2)
Section: Complete Segmentation Systems Based on Ohlander Technique (H2)
* Color Pixels Classification in an Hybrid Color Space
* Computational Techniques in the Visual Segmentation of Static Scenes
* Detection of Defects in Colour Texture Surfaces
8 for Color Segmentation

Color Sensors Section: Color Sensors, Sensor Models (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)

Color Texture Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Color Textures and Texture with Color (H2)

Color to Gray Section: Colorization, Gray, Color-to-Gray, Color Models (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)

Color Transfer Section: Color Transfer, Color Enhancement, Color Correction (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)

Color Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Color and Its Use in Computer Vision (H1)
Section: Color Compression, Multispectral Image Coding and Compression (H2)
Section: Color Edge Detectors (H1)
Section: Color Image Quality, Hyperspectral Image Quality (H3)
Section: Color in Image Enhancement (H2)
Section: Color Textures and Texture with Color (H2)
Section: Color, General Issues (H2)
Section: Color, Multispectral, RGB, for Salient Regions (H4)
Section: Complete Segmentation Systems Based on Ohlander Technique (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Database Indexing Using Color and Shape or Regions (H3)
Section: Database Indexing Using Color (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Face Analysis, Shading, Illumination, Lighting and Color Variations (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Finding Faces by Color Features (H3)
Section: Finding Objectionable Images, Harmful Content, Filtering Web Sites (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Skin Color Models, Skin Detection (H3)
Section: Texture and Color, Color and Texture, for Segmentation (H2)
Section: Tracking Faces, Heads Using Color Models (H3)
Section: Video Database Indexing, Color Analysis, Object Appearance (H4)
* Application of Color Information to Visual Perception
* ARGOS Image Understanding System, The
* Automatic Watershed Segmentation of Randomly Textured Color Images
* Color Image Processing for Navigation: Two Road Trackers
* Color Metric for Computer Vision, A
* Color Vision Cells Found in Visual Cortex
* Color-Encoded Structured Light for Rapid Active Ranging
* Computer Image Segmentation: Structured Merge Strategies
* Extracting Shape and Reflectance of Hybrid Surfaces by Photometric Sampling
* Face Detection and Gesture Recognition for Human-Computer Interaction
* From Image Measurements to Object Hypotheses
* Measurement Techniques for Spectral Characterization for Remote Sensing
* Picture Segmentation Using a Recursive Region Splitting Method
* Results Using Random Field Models for the Segmentation of Color Images
* Scene Segmentation by Cluster Detection in Color Space
* Semantic-Free Approach to 3-D Robot Color Vision, A
* vision system for automatic inspection of meat quality, A
46 for Color

Color, Edges Section: Color Edge Detectors (H1)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)

Color, Face Recognition Section: Face Analysis, Shading, Illumination, Lighting and Color Variations (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)

Color, Shape Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Shape Using Color Images, Color Photometric Stereo (H2)

Color, Transforms Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Production System for Region Analysis, A

Colorization Section: Colorization, Gray, Color-to-Gray, Color Models (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)

Combination Section: Classifier Combination, Evaluation, Overview, Appliction Specific (H4)
Section: Decision Fusion (H3)
Section: Hierarchical Combination, Multi-Stage Classifiers (H4)
Section: Multiple Classifiers Applied to Arabic Numbers (H4)
Section: Multiple Classifiers, Combining Classifiers, Combinations (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
7 for Combination

Comics Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Speech Ballons in Comics, Comic Analysis, Panel Detection (H4)

Commercial Detection Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Video Analysis, Find Ads, Find Commercials (H4)

Communication Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Section: Transmission Issues, MIMO, Communication (H3)

Comparisons Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Classifier, Performance Evaluation, Errors, Comparisons (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Experimental Comparison of Neural and Statistical Nonparametric Algorithms for Supervised Classification of Remote Sensing Images, An
* Experimental Comparison of Range Image Segmentation Algorithms, An

Complexity Analysis Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Faster Neighbor Finding on Images Represented By Bincodes

Complexity Section: Computational Complexity Issues (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)

Compressed Images Section: Halftone Images, Compressed Images: Image Hiding, Data Hiding, Steganography (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Reversible Data Hiding for JPEG, Steganography (H3)

Compressed Sensing Section: Coded Aperture Compressive Sensing (H2)
Section: Compressive Sensing, Compressive Imaging, Compressed Sensing, Compression, Reconstruction (H2)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)

Compression * *Image and Video Compression
* *Still-Image Compression
* *Visual Communications and Image Processing '96
* *Visual Information Processing V
Section: Adaptive Coding Techniques (H2)
Section: Architectures and Systems for Matching for Block Coding, Block Motion Estimation (H4)
Section: Audio and Video Coding Standard, AVS Coding Issues, Standards (H3)
Section: AVC/H.264 Mode Selection, Mode Decision (H4)
Section: Block Coding, Using Block Matching (H4)
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Coding -- Coding Theory, Communications, etc. (H2)
Section: Coding, Compression, Acoustic Signals, Sounds, Audio (H3)
Section: Color Quantization of Images (H4)
Section: Computation and Matching for Block Coding, Block Motion Estimation (H4)
Section: Computation and Matching for Region Coding (H4)
Section: Computation for General Motion Compensation, Motion Estimation (H4)
Section: Computation for Motion Compensation, Block and Region Coding (H3)
Section: Computation for Vector Fields, Flow Fields (H4)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Computing Very Low Bitrate, 3-D and Object Based Coding (H4)
Section: Cosine Transform, DCT Compression (H2)
Section: Differential Pulse Code Modulation (DPCM) Coding (H2)
Section: Document Compression, Document Coding Systems and Techniques (H2)
Section: Entropy Based Vector Quantization (H3)
Section: Fractal Based Coding and Compression, Fractal Coding, Fractal Compression (H3)
Section: Full Search Block Motion Estimation, Motion Coding (H4)
Section: General Rate-Quality, Rate Distortion, Rate Control, Error Tradeoffs for Video (H3)
Section: Global Motion Compensation (H4)
Section: H.264/AVC Issues, Advanced Video Coding (H3)
Section: Hierarchical, Multi-Level, Pyramidal Coding Techniques (H2)
Section: High Efficiency Video Coding, HEVC Coding Standards (H4)
Section: High Rate Compression, Low Bit Rate Compression, Region Based Coding (H2)
Section: Huffman Coding (H2)
Section: Image Compression, Coding, Overview Section (H1)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Image Quantization, Quantization of Images (H3)
Section: Intra-Coding, Intra-Prediction Issues, AVC/H.264 (H4)
Section: JPEG 2000, Discussion, Generation, and Use, JPEG2000 (H4)
Section: JPEG Standards and Use (H3)
Section: Learning, Neural Nets for Coding, Compression in Video (H2)
Section: Matching Pursuits, Video Coding (H2)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Motion and Video Coding: General (H1)
Section: Motion and Video Coding: Hardware and Systems (H2)
Section: Motion Compensation for Coding (H4)
Section: Motion Compensation, Block, Region, Object, and Low Bit Rate Coding (H2)
Section: Moving Image Coding, Compression: Using Vector Fields, Flow Fields (H4)
Section: MPEG 4 Issues (H3)
Section: MPEG 7 Issues (H3)
Section: MPEG and Related Standard Coding Methods (H2)
Section: Multi Dimensional Coding, Stereo Coding, Disparity Maps, 3-D Shapes (H2)
Section: Neural Net Compression (H4)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Point Cloud Compression (H3)
Section: Predictive, Adaptive Vector Quantization (H3)
Section: Rate-Quality, Rate Distortion for DCT Coded Images, Wavelet Coding (H4)
Section: Rate-Quality, Rate Distortion, Rate Control, Error Tradeoffs for AVC/H.264 (H4)
Section: Scalable Video Coding, SVC, Extensions AVC/H.264 (H4)
Section: Set Partitioning in Hierarchical Trees (SPIHT) Coding (H3)
Section: Subband Coding Techniques (H3)
Section: Tone Mapping of Images (H4)
Section: Transform Coding -- General (H2)
Section: Using Arbitrary Region Coding (H4)
Section: Using Motion Compensation, Block and Region Coding (H3)
Section: Variable Size Blocks for Block Coding, Block Motion Estimation (H4)
Section: Vector Quantization Survey and General (H3)
Section: Vector Quantization with other Transform Coding Methods (H3)
Section: Vector Quantization, VQ, Applied to Motion and Video Coding (H2)
Section: Vector Quantization, VQ, Image Compression (H2)
Section: Very Low Bitrate, 3-D and Object Based Coding (H4)
Section: VVC Issues, Versatile Video Coding Standard (H3)
Section: Wavelet Coding, Compression Applications, Hardware (H4)
Section: Wavelets for Image Coding -- Zero Tree Code (H4)
Section: Wavelets for Image Coding, Compression -- Block, Region and Shape Based (H4)
Section: Wavelets for Image Coding, Compression -- Quantization Issues (H4)
Section: Wavelets for Image Compression, Image Coding (H3)
Section: Wavelets for Motion and Video Coding (H3)
* Compression of Personal Identification Pictures Using Vector Quantization with Facial Feature Correction
* Digital Pictures: Representation, Compression, and Standards
* Extreme Compression of Weather Radar Data
* Handbook of Data Compression
* illumination invariant algorithm for subpixel accuracy image stabilization and its effect on MPEG-2 video compression, An
* Image Compression Using the 2-D Wavelet Transform
* Image Data Compression: Block Truncation Coding
87 for Compression

Compression, Binary Images Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Processing and Analysis of Binary (Two Level) Images (H1)

Compression, Color Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Color Compression, Multispectral Image Coding and Compression (H2)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Compression of Color Image via the Technique of Surface Fitting

Compression, Lossless Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Lossless Coding, Lossless Compression, Transmission (H2)

Compression, Model-Based Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Model-Based Image-Coding: Advanced Video Coding Techniques for Very-Low Bit-Rate Applications

Compression, Point Cloud Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Point Cloud Compression (H3)

Compression, Stereo Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Multi Dimensional Coding, Stereo Coding, Disparity Maps, 3-D Shapes (H2)

Compression, Video * *Digital Video Compression: Algorithms and Technologies 1995
Section: Architectures and Systems for Matching for Block Coding, Block Motion Estimation (H4)
Section: Audio and Video Coding Standard, AVS Coding Issues, Standards (H3)
Section: AVC/H.264 Mode Selection, Mode Decision (H4)
Section: Block Coding, Using Block Matching (H4)
Section: Computation and Matching for Block Coding, Block Motion Estimation (H4)
Section: Computation and Matching for Region Coding (H4)
Section: Computation for General Motion Compensation, Motion Estimation (H4)
Section: Computation for Motion Compensation, Block and Region Coding (H3)
Section: Computing Very Low Bitrate, 3-D and Object Based Coding (H4)
Section: Distributed Video Coding (H2)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Full Search Block Motion Estimation, Motion Coding (H4)
Section: Global Motion Compensation (H4)
Section: H.264/AVC Issues, Advanced Video Coding (H3)
Section: HDTV Issues, Coding, Transmission (H3)
Section: High Efficiency Video Coding, HEVC Coding Standards (H4)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Motion and Video Coding: General (H1)
Section: Motion and Video Coding: Hardware and Systems (H2)
Section: Motion Coding, Video Coding, Evaluations, Surveys (H2)
Section: Motion Compensation for Coding (H4)
Section: Motion Compensation, Block, Region, Object, and Low Bit Rate Coding (H2)
Section: Moving Image Coding, Compression: Using Vector Fields, Flow Fields (H4)
Section: MPEG 4 Issues (H3)
Section: MPEG 7 Issues (H3)
Section: MPEG and Related Standard Coding Methods (H2)
Section: Multiview Video Coding, Stereo Video Coding, 3D Video Coding (H2)
Section: Scalable Video Coding, SVC, Extensions AVC/H.264 (H4)
Section: Transmission, Television, and Television Coding (H2)
Section: Using Arbitrary Region Coding (H4)
Section: Using Motion Compensation, Block and Region Coding (H3)
Section: Variable Size Blocks for Block Coding, Block Motion Estimation (H4)
Section: Very Low Bitrate, 3-D and Object Based Coding (H4)
* Method of Coding TV Signals Based on Edge Detection, A
35 for Compression, Video

Compressive Sensing Section: Coded Aperture Compressive Sensing (H2)
Section: Compressive Sensing, Compressive Imaging, Compressed Sensing, Compression, Reconstruction (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Convolutional Network, Deep Networks, Learning for Compressive Sensing (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Light Field Compressed Sensing (H3)

Computation Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Tensor Completion (H4)

Computational Complexity Section: Computational Complexity Issues (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)

Computational Vision Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: General Computational Vision (H1)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Bayesian-approach to Binocular Stereopsis, A
* From Pixels to Predicates
* Ill-Posed Problems and Regularization Analysis in Early Vision
7 for Computational Vision

Computational Vision, Survey Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Computational Approaches to Image Understanding
* Computational Vision
* Integration of Visual Modules: An Extension of the Marr Paradigm

Computer Icons Section: Analysis of Graphics, Symbols, Trademarks, Icons (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)

Concavity Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Concavity Detection (H3)

Concrete Inspection Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Pavement, Road Surface, Asphalt, Concrete (H4)

Cone-Beam Tomography Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Tomographic Image Generation, Cone-Beam, Fan-Beam, Helical, Spiral Reconstruction (H2)

Conference Reports Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Conference Listings or Special Issues, Introductions through 2004 (H1)
Section: Conference Listings or Special Issues, Introductions, 2005-2009 (H2)
Section: Conference Listings or Special Issues, Introductions, 2010-2012 (H2)
Section: Conference Listings or Special Issues, Introductions, 2013-2015 (H2)
Section: Conference Listings or Special Issues, Introductions, 2016-2018 (H2)
Section: Conference Listings or Special Issues, Introductions, 2019-2022 (H2)
Section: Conference Listings or Special Issues, Introductions, 2023- (H2)
8 for Conference Reports

Conferences Section: Conference Names, Index of Frequent Conferences (H1)

Congestion Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Traffic Collisions, Accidents, Analysis, Congestion, Not Image Analysis (H4)

Connected Components Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Extraction and Analysis of Connected Components and Boundaries (H1)
* Sequential Operations in Digital Picture Processing

Connected Vehicles Section: Connected Vehicles, Use, Evaluation (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)

Connection Machine Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Object Recognition Using the Connection Machine
* Parallel Integration of Vision Modules
* Recognition Algorithms for the Connection Machine

Connectionist Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Connectionist Approaches to Computer Vision (H1)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Connectionist Approach for Gray Level Image Segmentation, A
* Symbolic Mapping of Neurons in Feedforward Networks

Connectivity Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Extraction and Analysis of Connected Components and Boundaries (H1)
* Efficient Evaluations of Edge-Connectivity and Width Uniformity

Constraint Satisfaction Section: Continuous Relaxation Theory, Constraint Satisfaction (H3)
Section: Discrete Relaxation Methods (H2)
Section: Discrete Relaxation Theoretical Issues (H3)
Section: Evidence Theory, Combination Techniques, Optimization Techniques (H3)
Section: Faugeras and Berthod Gradient Optimization Methods (H3)
Section: General Structure and Graph Representation, Relations, Neighbors (H2)
Section: Graph Matching Theoretical Issues (H2)
Section: Graph Matching, Continuous Relaxation, Constraint Satisfaction (H2)
Section: Graph Matching, Neural Networks, Hopfield Networks (H2)
Section: Hummel and Zucker Relaxation Papers (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Matching Using Tree Searching Techniques, Heuristic Search (H2)
Section: Shmuel Peleg Theoretical Relaxation Papers (H3)
* Bit-vector Algorithms for Binary Constraint Satisfaction and Subgraph Isomorphism
* Linear Programming Approach to Max-Sum Problem: A Review, A
* Model Based Pose Estimation of Articulated and Constrained Objects
16 for Constraint Satisfaction

Constraint Satisfaction, Survey Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Algorithms for Constraint-Satisfaction Problems: A Survey

Contactless Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Touchless Palmpring, Contactless Palmprints (H2)

Context Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Context and Structure for Classification (H2)
Section: Context in Computer Vision (H2)
Section: Context, Fine-Grained Classification (H3)
Section: Fine-Grained Classification Using CNN, Convolutional Neural Networks (H4)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Techniques for Model Guided Segmentation, Context in Segmentation (H1)
* Interpretation of Remotely Sensed Images in a Context of Multisensor Fusion
10 for Context

Continual Learning Section: Continual Learning (H4)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Contour Coding Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Contour Coding, Boundary Coding (H2)

Contour Completion Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Contour Completion, Subjective Contours (H3)

Contour Matching Section: 2-D Contour Matching, Indexing or Hashing Techniques (H3)
Section: 2-D Region or Contour Matching (H2)
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Contours Through a Sequence (H3)
Section: Hierarchical/Scale-Space Contour Matching and Descriptions (H3)
Section: Jigsaw Puzzle Solving, 2-D Region or Contour Matching (H3)
Section: Partial Contour Matching, Piecewise Segments (H3)
Section: Piecewise Segment Matching of Contours (H2)
Section: Region or Contour Invariants, Signatures, Metrics for Matching (H3)
Section: Region/Contour Matching, Accumulation Based (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Snakes, Matching Deformable Contours (H3)
Section: String Matching, Syntatic Matching (H3)
Section: Tracking Applied to Heart Images (H3)
Section: Tracking Deformable Shapes (H3)
15 for Contour Matching

Contour Tracing Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Contour Representation of Binary Images Using Run-type Direction Codes

Contourlet Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Contourlet Representations and Processing (H2)

Contours Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Optical Flow Along Contours (H2)
Section: Optical Flow Field Computations and Use (H)
Section: Surface and Shape from Contours or Silhouettes (H1)
Section: Waveform and Contour Analysis (H2)

Contrast Enhancement Section: Contrast Enhancement (H2)
Section: Histogram Equalization, Image Enhancement, Contrast Enhancement (H3)
Section: Image Enhancement for Display, Printers, High Dimensional Visualization (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)

Contrast Section: Contrast Enhancement (H2)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)

Contrastive Learning Section: Contrastive Learning (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Control Systems Section: Control Systems, Feedback Control, Systems Analysis (H2)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)

Convective Storm Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Convective Storm Analysis, Weather Radar Applications (H4)

Convex Hull Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Convex Hull Algorithms and Convexity Analysis (H2)
Section: Convex Hull of Polygons (H3)

Convex Polygon Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* On Limit Properties in Digitization Schemes

Convexity Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Convex Hull Algorithms and Convexity Analysis (H2)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Morphological Decomposition of 2-D Binary Shapes into Conditionally Maximal Convex Polygons

Convolution Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Implementation of Convolution and Smoothing Techniques (H3)

Convolutional Neural Network Section: Convolutional Neural Network, CNN, Re-Identification Issues, Pedestrian Tracking (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)

Convolutional Neural Networks Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Convolutional Network, Deep Networks, Learning for Compressive Sensing (H3)
Section: Convolutional Neural Networks for Human Action Recognition and Detection (H4)
Section: Convolutional Neural Networks for Image Descriptions, Classification (H3)
Section: Convolutional Neural Networks for Object Detection and Segmentation (H4)
Section: Convolutional Neural Networks for Semantic Segmentation, CNN (H4)
Section: Convolutional Neural Networks, Design, Implementation Issues (H4)
Section: Data Hiding, Steganography, Adversarial Networks, Convolutional Networks, Deep Learning (H3)
Section: Fine-Grained Classification Using CNN, Convolutional Neural Networks (H4)
Section: Forgetting, Learning without Forgetting, Convolutional Neural Networks (H4)
Section: Graph Convolutional Neural Networks (H4)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Intrepretation, Explaination, Understanding of Convolutional Neural Networks (H4)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Single View 3D Reconstruction, Convolutional Neural Networks, CNN (H3)
Section: Training Issues for Convolutional Neural Networks (H4)
20 for Convolutional Neural Networks

Cooperating Robots Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Coordinating Motion of Cooperative Mobile Robots Through Visual Observation

Copy Detection Section: Image Copy, Duplicate Image Detection (H4)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Video Copy, Video Duplicate Detection (H4)

Copy Move Section: Copy-Move Tamper Detection, Forensics (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)

Copyright Protection Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Watermarks for Copyright, Ownership Protection, Authentication, Verification (H2)

Coral Reef Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Coral Reef Mapping, Analysis (H2)

Corn Classification Section: Maize or Corn Crop Analysis, Production, Detection, Health, Change (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Corn Yield Section: Maize or Corn Crop Analysis, Production, Detection, Health, Change (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Cornea Section: Eye, Cornea, Corneal Images (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Corneal Images Section: Eye, Cornea, Corneal Images (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Corner Detection Definition:* Locating the discontinuities in smooth curves, especially used to create polygonal representations of curves. Also detecting 2-D features where, roughly speaking, one quadrant of the region around the point differs from the other three.
Section: Corner Feature Detection Techniques and Use (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Direct Curvature Scale Space: Theory and Corner Detection

Corner Detector Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Corner Feature Detection Techniques and Use (H3)
Section: Curvature, Corners, Dominant Points, Salient Points, Junctions (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Assessing the performance of corner detectors for point feature tracking applications
* Local Symmetries of Digital Contours from Their Chain Codes
* Role of Key-Points in Finding Contours, The
* Steerable-Scalable Kernels for Edge Detection and Junction Analysis
* Volumetric Model and 3D Trajectory of a Moving Car from Monocular TV Frames Sequence of a Street Scene
12 for Corner Detector

Corner Detector, Evaluation Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Corner Detection Using the Facet Model

Corner Matching Section: Image Registration -- Using Edges, Lines, Curves, and Corner and other Features (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)

Coronary Artery Section: Medical Applications -- Coronary Arteries, Carotid Arteries (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Coronary Vessels Section: Medical Applications -- Coronary Arteries, Carotid Arteries (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)

Correlation Filter Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Target Tracking Techniques, Filter Techniques, Correlation (H3)

Correlation Matching Section: Correlation Based and Signal Matching Techniques (H2)
Section: Matching for Stereo, Correlation (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)

Cortex Section: Brain Waves, EEG Analysis, Electroencephalogram for Biometrics (H3)
Section: Brain, Cortex, Alzheimer's Disease (H3)
Section: Brain, Cortex, Brain Waves, EEG Analysis, Electroencephalogram (H2)
Section: Brain, Cortex, Dementia (H2)
Section: Brain, Cortex, MRI Analysis, Models, 3-D (H2)
Section: Brain, Cortex, MRI Segmentation (H3)
Section: Brain, Cortex, Registration, Alignment, MRI, Other (H3)
Section: Brain, Parkinson's Disease (H2)
Section: Brain, Schizophrenia (H2)
Section: Brain, Stroke, Ischemic Stroke (H2)
Section: Medical Applications -- Brain, Cortex Applications (H1)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: White Matter Fiber Tractography MRI (H3)
* Cortical Surface Reconstruction Using a Topology Preserving Geometric Deformable Model
14 for Cortex

Cosine Transform Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Cosine Transform, DCT Compression (H2)
Section: DCT Block Coding -- Block Artifacts in DCT (H4)
Section: DCT Computation (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)

Cotton Section: Cotton, Analysis and Change (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Count Objects Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Counting Instances, Counting Objects (H3)

Counting People Section: Counting People, Crowds, Crowd Counting (H4)
Section: Counting People, Transportation System Monitoring, Queues (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Multi-Modal Crowd Counting (H4)
Section: Multi-Scale, Scale Aware Crowd Counting (H4)

Counting Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Counting Instances, Counting Objects (H3)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Vehicle Counting (H3)

Covariance Propagation Section: Books, Collections, Overviews, General, and Surveys (H)
* Propagating Covariance in Computer Vision

Covid Section: GIS: for COVID Specific Tracking, Spread, Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Pneumonia, Lung Analysis, Flu, COVID (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Crack Detection Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Defect Detection, Crack Detection (H3)
Section: Inspection -- Pavement, Road Surface, Asphalt, Concrete (H4)

Cracks Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Markov Fusion of a Pair of Noisy Images to Detect Intensity Valleys

Crater Detection Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Crater Detection, Impact Craters, Depressions (H3)

CRF Definition:* Conditional Random Fields.

Cricket Section: Baseball, Cricket, Tracking, Desctiptions, Analysis (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)

Crime Data Section: GIS: Crime Data Analysis and Representation (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

CrisisMMD Dataset * *CrisisMMD Dataset
Section: OCR, Document Analysis and Character Recognition Systems (H)

Crop Classification Section: Classification for Crops, Analysis of Production, Specific Crops, Specific Plants (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Crop Residue Section: Crop Residue Analysis (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Crop Yield Section: Classification for Crops, Analysis of Production, Specific Crops, Specific Plants (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Cropland Abandonment Section: Cropland Abandonment, Change Due to Abandonment (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Crops Section: Aquaculture, Analysis, Extraction (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Cross-Domain Section: Domain Adaption, Cross-Domain, Learning, Re-Identification Issues (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)

Cross-Modal Biometrics Section: Biometrics, Cross-Modal, Multi-Modal Systems, Multibiometrics, Combined Face and Other Features, Fusion (H2)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)

Cross-Modal Counting Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Multi-Modal Crowd Counting (H4)

Cross-Modal Fusion Section: Fusion, General Multi-Modal (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)

Cross-Modal Retrieval Section: Cross-Modal Indexing, Cross-Modal Retrieval (H2)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)

Cross-Modal Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Multi-Modal, Cross-Modal Captioning, Image Captioning (H3)

Crosswalks Section: Crosswalk Detection, Zebra Crossings (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)

Crowd Behavior Section: Human Activities, Crowds, Lots of People (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)

Crowd Counting Section: Counting People, Crowds, Crowd Counting (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Multi-Modal Crowd Counting (H4)
Section: Multi-Scale, Scale Aware Crowd Counting (H4)

Crowds Section: Crowds, Tracking Multiple People, Multiple Pedestrian Tracking (H4)
Section: Detecting Anomalies, Abnormal Behavior In Crowds (H4)
Section: Human Activities, Crowds, Lots of People (H4)
Section: Human Activities, Tourist Traffic Flow (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)

Crowdsource Section: Remote Sensing General Issue, Land Use, Land Cover (H)
* Estimating Regional Snow Line Elevation Using Public Webcam Images

Crowdsourced Section: GIS: Volunteered Geographic Information, Open Access, Crowd Sourcing, Crowdsource (H2)
Section: GIS: Volunteered Geographic Information, OpenStreetMap, Open Street Map (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Crowdsourcing Section: Crowdsourcing, Recognition, Analysis, Descriptions (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Crowdsourcing in Computer Vision

Crowns Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Tree Crowns, Crown Shape, Crown Delineation (H3)

Cruise Control Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Adaptive Cruise Control (H4)
Section: Car Following Control, Leader-Follower Control (H4)
Section: Overtaking Analysis, Control (H4)

CRULE Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Novel Approach to Colour Constancy, A

Cryptography Section: Encryption, Visual Cryptography, Authentication (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)

CT Section: Heart, Cardiac, Angiography using CAT, CT, Tomography (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Tomographic Image Generation, CAT, CT, Reconstruction (H2)
Section: Tomographic Images, CAT Scans (Computed Axial Tomography) (H1)
Section: Tomographic Images, CAT, CT, Overviews, Surveys, Datasets (H2)
Section: Tomographic Object Construction, Object Extraction, Analysis, Organs (H2)

Cultural Heritage Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Archeological Sites, Modeling, Analysis, Tools (H2)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Cultural Heritage Modeling Systems, Laser, LiDAR (H3)
Section: Cultural Heritage Models, General Systems, Modeling Systems (H3)
Section: Cultural Heritage Sites, Modeling, Analysis, Large Scale Models (H2)
Section: Cultural Heritage Sites, Modeling, Specific Models: Europe (H3)
Section: Cultural Heritage, Museum Visitation Models, Immersive, Augmented Reality, Virtual Reality (H4)
Section: Cultural Heritage, Museum Visitation Models, Tour Guide, Visualization (H3)
Section: Ground Penetrating Radar for Archeological Sites (H3)
Section: Historical Document Analysis, Ancient Documents (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Specific 3-D Models, Cultural Items, Applied 3-D Descriptions (H2)
Section: Specific 3-D Models, Paintings, Murals, Frescoes (H2)
Section: Specific 3-D Models, Rock Art, Petroglyphs, Rock Structures, Caves (H2)
Section: Specific 3-D Models, Vaulted Structures (H3)
Section: Specific Museum Visitation Models, Tour Guide, Visualization (H4)
* ISHIGAKI Retrieval System Using 3D Shape Matching and Combinatorial Optimization
19 for Cultural Heritage

Curb Detection Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Curb Detection, Street Boundaries (H3)

Curcuit Inspection Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Inspection -- Chips, Wafers, PCB, PWB, VLSI, IC, Disks, etc. (H3)

Curls Section: Enhancement, Restoration of Document Images, Curls (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)

Currency Section: Money and Check Processing -- Amounts, etc. (H2)
Section: OCR, Document Analysis and Character Recognition Systems (H)

Currents Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Downwelling, Upwelling Analysis, Oceans, Lakes, Water (H4)
Section: Ocean Currents, Costal Surface Currents (H3)
Section: Oceanic Eddy Currents, Eddies (H4)

Cursive Character Recognition Section: Cursive Script, Word Level Recognition, Word Spotting, Language Model (H4)
Section: Handwriting, Cursive Script Recognition Systems (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: On-Line Cursive Script Recognition Systems (H4)

Cursive Script Section: OCR, Document Analysis and Character Recognition Systems (H)
* On-Line Cursive Word Recognition System, An
* Recognizing Off-Line Cursive Handwriting

Curvature Analysis Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Curvature and Features of Surfaces and Range Data (H2)
Section: DEM, Surface Analysis for Ridges and Streams, Rivers, Drainage, Depressions (H2)

Curvature Three-Dimensional Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Generic Curvature Features from 3-D Images

Curvature Section: Curvature, Corners, Dominant Points, Salient Points, Junctions (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Features for Contour Matching (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)

Curvature, Surfaces Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Curvature and Features of Surfaces and Range Data (H2)

Curve Description Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Local Symmetries of Digital Contours from Their Chain Codes

Curve Evolution Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Active Contours, Snakes or Deformable Curves (H2)
Section: Snakes, Algorithms for Computation (H3)
Section: Snakes, Applications (H3)
Section: Snakes, General Techniques and Descriptions (H3)
Section: Snakes, Restricted Curves, Splines, etc. (H2)

Curve Fitting Section: Curve Fitting (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)

Curve Partitions Section: Basic Algorithms to Partition Curves, Represent Curves (H2)
Section: Basic Algorithms to Partition Curves, The Early Days (H2)
Section: Curve Partitions, Applied to Chain Codes (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Generation of Straight Line Segments or Curve Partitions (H1)
Section: Parallel Algorithms, Curve Partition (H3)

Curve Representations Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Generalized Uniqueness Wavelet Descriptor for Planar Closed Curves, The

Curve Segmentation Section: Basic Algorithms to Partition Curves, Represent Curves (H2)
Section: Basic Algorithms to Partition Curves, The Early Days (H2)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)

Curvelet Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Curvelet Transform (H2)

Curves, General Section: Curve Fitting (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: General Systems for Lines and Curves (H2)

Cut Detection Section: Cut Detection in Compressed Images, MPEG, Video Analysis (H4)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Video Analysis, Cut Detection, Scene Segmentation, Shot Detection, Shot Boundary (H3)

Cyanobacteria Section: Cyanobacteria, Analysis, Detection (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)

Cybersickness Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Section: Three Dimensional Displays, Viewer Fatigue, Sickness, Comfort, Aesthetics (H2)

Cyclic Motion Section: Cyclic Motion, Periodic Motion, Symmetric, for Walking and Gait Recognition (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: Walking, Gait Recognition, University of Southampton (H4)
* Cyclic Motion Detection for Motion Based Recognition

Cyclone Section: Cyclones, Hurricanes, Typhoons, Radar, Cloud analysis (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)

Cylinders Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Cylinders, Application Tanks (H3)
Section: Generalized Cylinders, Medial Axis Descriptions (H1)

Index for "d"


Last update:16-Mar-24 20:56:33
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