Object-Based
Section: Object Based Land Cover, Parcels, Region Based Land Cover, Land Use Analysis (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Smallholder Analysis (H4)
Object-Oriented Programming
Section: Books, Collections, Overviews, General, and Surveys (H)
* Pattern Recognition and Image Processing in C++
Object Descriptions
Section: Learning Object Descriptions, Object Recognition (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Object Detction
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Feature and Object Detection Systems (H2)
Section: One-Shot Object Detection, Single Shot Detector, and Segmentation (H3)
Section: Remote Sensing Object Detection Applications (H3)
Section: Semi-Supervised Object Detection (H3)
Section: SWIN Transformer (H4)
Section: YOLO, You Only Look Once, Family Object Detection (H4)
7 for Object Detction
Object Detection
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 Object Detection and Reconstruction from Video (H2)
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, Multispectral, RGB, for Salient Regions (H4)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Convolutional Neural Networks for Object Detection and Segmentation (H4)
Section: Dense Object Detection (H3)
Section: Depth Object Detection, 3D Object Detection (H3)
Section: Depth Object Segmentation, Point Cloud Segmentation (H3)
Section: Detection of Moving Objects from Image Sequences or Video (H2)
Section: Factorizationm, Non-Rigid Motion, Object, Structure, University of London (H2)
Section: Monocular 3D Object Detection (H3)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Object Proposals, Initial Points, Proto-Objects, Candidates (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: RGB and Thermal Fusion for Object Extraction (H4)
Section: Road Scene, General Analysis (H4)
Section: Salient Regions, Convolutional Neural Networks, Deep Nets (H4)
Section: Salient Regions, Saliencey for Regions (H3)
Section: Self-Supervised Learning for Object Detection and Segmentation (H3)
Section: Semantic Object Detection, 3D, Depth (H3)
Section: Semi-Supervised Object Detection, 3D Object Detection (H3)
Section: Semi-Supervised Video Object Segmentation (H4)
Section: Small Objects, Detect Small Objects (H3)
Section: Spot Detection, Bright Spots (H3)
Section: Underwater Object Detection (H4)
Section: Video Object Segmentation (H3)
Section: Weakly Supervised, Unsupervised Salient Regions (H4)
31 for Object Detection
Object Extracton
Section: Multi-View Object Detection, Object Extraction (H2)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Object Insertion
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Merging Views, Object Insertion in Image (H3)
Object Localization
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Object Localization (H3)
Object Matching
Section: Computing Very Low Bitrate, 3-D and Object Based Coding (H4)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Very Low Bitrate, 3-D and Object Based Coding (H4)
Object Proposals
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Object Proposals, Initial Points, Proto-Objects, Candidates (H3)
Object Recognition
Section: 3-D Object Recognition from Pose Estimation or Alignment (H2)
Section: 3-D Object Recognition Using Invariants (H2)
Section: ACRONYM and SUCCESSOR Papers - Stanford University and Others (H2)
Section: Active Appearance Models: AAM (H3)
Section: Aspect Graph Matching -- Bowyer (H3)
Section: Aspect Graph Matching -- Ikeuchi (H3)
Section: Aspect Graph Matching, Characteristic Views (H2)
Section: Aspect Graphs, Matching Systems, Object Recognition (H3)
Section: Associative Memory for Matching and Recognition (H3)
Section: Basic Comparison of Relational Network Descriptions (H2)
Section: Context in Computer Vision (H2)
Section: Discrete Relaxation Methods (H2)
Section: General Structure and Graph Representation, Relations, Neighbors (H2)
Section: Graph Matching and Relaxation (H1)
Section: Graph Matching, Continuous Relaxation, Constraint Satisfaction (H2)
Section: Graph Matching, Neural Networks, Hopfield Networks (H2)
Section: Grimson Object Recognition Papers (H3)
Section: Invariance Papers -- Mundy (H3)
Section: Invariants -- Eigen Representations, General Appearance Based Methods (H2)
Section: Invariants -- ICA, Independent Component Analysis (H3)
Section: Invariants -- Linear Discriminant Analysis, Fisher Linear Discriminant (H3)
Section: Invariants -- Principal Component Analysis (H3)
Section: Invariants, General Issues and Techniques (H3)
Section: Knowledge-Based Vision (H1)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Matching Graphs and 3-D Network Descriptions (H2)
Section: Matching Using Accumulation and Alignment Schemes (H2)
Section: Matching Using Tree Searching Techniques, Heuristic Search (H2)
Section: Model Based Recognition Systems (H2)
Section: Object Recognition, General Techniques (H1)
Section: Open Set, Open World Recongnition (H2)
Section: Other Sparse Coding, Low Dimensional Representation, Invariants (H3)
Section: Other, Kernel Methods, Invariants (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Recognition by Function, By Use, Affordance (H2)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Rule-Based or Expert Systems for Recognition (H2)
Section: Scene Graph Construction, Scene Graph Generation (H2)
Section: Sparse Descriptions, Dictionary Descriptions (H4)
Section: Three-Dimensional Matching Using Hashing/Indexing (H2)
Section: University of Massachusetts VISIONS System (H2)
* Computational Approaches for Processing and Analysis of Tactile Information
* Recognizing 3D Objects Using Tactile Sensing and Curve Invariants
43 for Object Recognition
Object Removal
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Inpainting, Video Inpainting (H4)
Section: Object Removal, Inpainting After Removing Objects (H4)
Object Segmentation
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Depth Object Segmentation, Point Cloud Segmentation (H3)
Section: Detection of Moving Objects from Image Sequences or Video (H2)
Section: Graph Cut Motion Segmentation, Background-Foreground Extraction (H3)
Section: Hough, Voting, Accumulation Methods for Moving Object Extraction (H3)
Section: Instance Segmentation, Point Cloud Segmentation (H3)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Moving Object Extraction Using Edges (H3)
Section: Moving Object Extraction with Moving Cameras (H3)
Section: Semi-Supervised Video Object Segmentation (H4)
Section: Video Object Segmentation (H3)
Section: Video Semantic Object Segmentation (H4)
12 for Object Segmentation
Object Tracking
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Region, Object, Target Tracking (H2)
Objectionable
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Finding Objectionable Images, Harmful Content, Filtering Web Sites (H3)
Oblique Images
Section: Buildings from Oblique Images (H2)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Obstacle Avoidance
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Obstacle Dectection, Objects on the Road (H3)
Section: Path Planning for Obstacle Avoidance (H4)
* Reactive Locomotion Control of a Tracked Mobile Manipulator
Obstacle Detection
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Airplane Obstacles, Collision Detection, Sense and Avoid (H3)
Section: Obstacle Dectection, Objects on the Road (H3)
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)
7 for Obstacle Detection
Obstacle Dtection
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Specialized Multibaseline Stereo Technique for Obstacle Detection, A
Occlusion
Section: Matching for Stereo, Occlusion, Discontinuity Analysis (H3)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Occlusions
Section: Discontinuous Optic Flow Computation, Occlusions (H2)
Section: Face Recognition Systems, Occlusions, Masks (H3)
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: Optical Flow Field Computations and Use (H)
Section: Target Tracking Techniques, Occlusions, Clutter (H4)
Section: Target Tracking, Multi-Object Tracking, Occlusions (H3)
Section: Tracking Formations, Groups, Multi-Object Tracking (H4)
Section: Tracking People, Re-Identification Issues, Occlusions (H4)
10 for Occlusions
Occupancy Grids
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Occupancy Grids, Voxels (H2)
Ocean Color
Section: Ocean Color Analysis, Ocean Colour Analysis, Water Quality (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Ocean Level
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Sea Level Measurement and Change, Satellite Altimetric Data (H2)
OCR
Definition:* Optical Character Recognition.
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Arabic Character Recognition (H3)
Section: Arabic Numbers, Digits, Handwritten, Numeral Recognition (H3)
Section: Arabic Recognition, Word Level, Word Spotting (H3)
Section: Character Recognition Survey, Overview, Evaluations (H2)
Section: Character Recognition Systems -- Korean Characters, Hangul (H2)
Section: Character Recognition Systems (H1)
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: Devanagari, Indic, Hindi, Hindu, Bangla, Bengali, Telugu, Characters (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Farsi, Persian Character Recognition (H3)
Section: Formulas, Equations, Mathematical Expressions, Mathematical Symbols (H3)
Section: General Character Recognition Issues (H2)
Section: Hidden Markov Models, HMM (H3)
Section: License Plate Recognition, Extraction, Analysis (H3)
Section: Mail -- Addresses, Document Analysis, Postal Automation (H2)
Section: Money and Check Processing -- Amounts, etc. (H2)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Multiple Classifiers Applied to Arabic Numbers (H4)
Section: Neural Networks for Numbers and Digits (H4)
Section: Numbers, Digits, Zip (Postal) Codes (H4)
Section: OCR Evaluations (H2)
Section: OCR Systems, General (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Online Recognition of Chinese Characters (H3)
Section: Other Character Sets (H2)
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: Roman Alphabet -- Machine Printed (H3)
Section: Roman Alphabet (H2)
* Bayesian Framework for Deformable Pattern Recognition with Application to Handwritten Character Recognition
* Evaluation of Pattern Classifiers for Fingerprint and OCR Applications
* IBM 1975 Optical Page Reader, Part II: Video Thresholding, The
* Image Thresholding for Optical Character Recognition and Other Applications Requiring Character Image Extraction
* Segmentation of Document Images
* Skeletonization for Fuzzy Degraded Character Images
* Statistical Syntactic Methods for High-Performance OCR
* What Size Test Set Gives Good Error Rate Estimates?
43 for OCR
Oct-tree
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Oct-Trees (or Octrees) and Voxels for Three-Dimensional Descriptions (H1)
OCT
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Retinal Images, Optical Coherence Tomography, OCT (H2)
Octree
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Oct-Trees (or Octrees) and Voxels for Three-Dimensional Descriptions (H1)
Section: Oct-Trees -- Theoretical Issues (H2)
Section: Oct-Trees -- Use (H2)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Recovering the Position and Orientation of Free-Form Objects from Image Contours Using 3D Distance Maps
* Survey of Construction and Manipulation of Octrees, A
7 for Octree
Octtree
Definition:* A representation technique for 3-D data that divides the volume into 8 blocks, then each of these into eighths, etc. Thus forming a tree with 8 branches at each level.
Odometry
Section: LiDAR Odometry, Distance Measurments from LiDAR (H3)
Section: Optical Flow Field Computations and Use (H)
Section: Visual Odometry, Distance Measurments from Vision, Motion (H3)
Odors
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Section: Smell, Olfactory, Odor Analysis, Taste (H2)
OFDM
Definition:* Orthogonal Frequency Division Multiplexing. Coding technique.
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Section: Transmission Issues, Orthogonal Frequency-Division Multiplexing, OFDM (H3)
Off-Road Navigation
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Road Following, Depth, Stereo Based, Off-Road, Safe Path (H3)
Off Line Signatures
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Off Line Signature Analysis (H4)
Office Environment
Section: Human Action Recognition, Office, Meetings (H4)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
OGC
Definition:* Open GeoSpatial Consortium.
Oil Slicks
Section: Oil Slicks, Oil Spills, Water Areas (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Oil Spills
Section: Oil Slicks, Oil Spills, Water Areas (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Oil Tanks
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Cylinders, Application Tanks (H3)
Olfactory
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Section: Smell, Olfactory, Odor Analysis, Taste (H2)
Olive
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Olive Trees, Orchards, Diseases (H4)
Omnidirectional Sensors
Section: Catadioptric Cameras (H4)
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: Omnidirectional and Panoramic Sensors (H3)
* Telepresence by Real-Time View-Dependent Image Generation from Omnidirectional Video Streams
Omnidirectional
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: Augmented Reality, With Panoramic, Omnidirectional Images (H3)
Section: Catadioptric, Omnidirectional Camera Calibration, Fisheye Lens (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Shape and Stereo from Panoramic Views, Stereo from Omnidirectional Images, Plenoptic (H1)
On-Demand Rides
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: On-Demand Ride Systems, Car Sharing, Taxi, Analysis (H4)
One-Shot Detection
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: One-Shot Object Detection, Single Shot Detector, and Segmentation (H3)
One-Shot Learning
Section: Face Recognition Systems from Single Example, One Sample, One Shot (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities (H)
Section: One Shot Learning (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Zero-Shot, One-Shot, Few-Shot Learning for Human Action Recognition (H4)
One Class
Section: One Class Clustering, One Class Classification (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Support Vector Machines, SVM, One-Class Classification (H3)
Online Handwriting
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: On-Line Cursive Script Recognition Systems (H4)
Online Recognition
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Online Recognition of Chinese Characters (H3)
Online Signatures
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: On-Line Signatures, Online Signatures (H3)
Online Systems
Section: Handwritten Characters, Cursive Script, Surveys, Data, Comparisons, Evaluations (H4)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: On-Line Cursive Script Recognition Systems (H4)
Section: Online Recognition of Handwritten Characters (H4)
Open-Pit Mines
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Open Pit Mines, Analysis, Detection (H4)
Open-Set Adaptation
Section: Open-Set Domain Adaptation (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Open-Set Objects
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Generic Object Detection, Open World, Open-Set, Open-Vocabulary (H3)
Open Data
Section: GIS: Volunteered Geographic Information, Open Access, Crowd Sourcing, Crowdsource (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Open Set Recognition
Section: Open Set, Open World Recongnition (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Open Set
Section: Open Set, Open World Recongnition (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Open World
Section: Open Set, Open World Recongnition (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
OpenStreetMap
Section: GIS: Volunteered Geographic Information, OpenStreetMap, Open Street Map (H2)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Optic Disc
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Optic Disc Location, Optic Disc Detection (H2)
Optic Flow
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* First Order Optic Flow from Log-Polar Sampled Images
Optical Coherence Tomography
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Retinal Images, Optical Coherence Tomography, OCT (H2)
Optical Floe
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Hyperspectral Meets Optical Flow: Spectral Flow Extraction for Hyperspectral Image Classification
Optical Flow
Definition:* The projection of the 3-D velocity field onto the 2-D image plane.
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Event Camera Opeical Flow (H2)
Section: Large Displacement Optical Flow (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (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)
Section: Motion with Optical Flow and Depth (H2)
Section: Opeical Flow, Learning, Neural Networks, GAN (H2)
Section: Optic Flow Computation and Use, Other Approaches (H1)
Section: Optical Flow Along Contours (H2)
Section: Optical Flow Field Computation -- General Issues (H1)
Section: Optical Flow Field Computation and Analysis (H1)
Section: Optical Flow Field Computations and Use (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Active Recovery of 3D Motion Trajectories and Their Use in Prediction, The
* Computation of Cloud-base Height from Paired Whole-Sky Imaging Cameras, The
* Determining Optical Flow
* Generalized Image Matching by the Method of Differences
* Interpretation of a Moving Retinal Image, The
* On the Estimation of Optical Flow: Relations between Different Approaches and Some New Results
* Physically-Based Adaptive Preconditioning for Early Vision
* Recognizing Functionality
23 for Optical Flow
Optical Flow, Binocular
* 3-D Translational Motion and Structure from Binocular Image Flows
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Optical Flow, Boundaries
Section: Optical Flow Field -- Boundaries (H2)
Section: Optical Flow Field Computations and Use (H)
Optical Flow, Contours
Section: Optical Flow Along Contours (H2)
Section: Optical Flow Field Computations and Use (H)
Optical Flow, Discontinuous
Section: Discontinuous Optic Flow Computation, Occlusions (H2)
Section: Optical Flow Field Computations and Use (H)
Optical Flow, Evaluation
Section: Error Analysis, Evaluation for Optical Flow (H1)
Section: Optical Flow Field Computations and Use (H)
* Analysis of Differential and Matching Methods for Optical Flow
* Gradient Based Estimation of Disparity
* Motion Segmentation and Estimation by Constraint Line Filtering
* On the Information in Optical Flows
Optical Flow, Features
Section: Egomotion or Ego Motion Computation from Flow Fields (H2)
Section: Focus of Expansion and Other Features (H2)
Section: Optical Flow Field Computations and Use (H)
Section: Point Matching for Optical Flow Computation (H2)
Optical Flow, Gradient Based
Section: Optical Flow Field Computation -- Gradient Techniques (H2)
Section: Optical Flow Field Computations and Use (H)
* Lower-level Estimates and Interpretation of Visual Motion
Optical Flow, Multigrid
Section: Optical Flow -- Hierarchical, Pyramid, Multi-Grid, Multi-Scale Approaches (H2)
Section: Optical Flow Field Computations and Use (H)
Optical Flow, Multiple Layers
Section: Optical Flow Field -- Boundaries (H2)
Section: Optical Flow Field -- Multiple Flows, Transparent Layers, Motion Layers (H2)
Section: Optical Flow Field Computations and Use (H)
Optical Flow, Multiple Motion
Section: Optical Flow Field Computations and Use (H)
* Layered Representation for Motion Analysis
Optical Flow, Occlusions
Section: Discontinuous Optic Flow Computation, Occlusions (H2)
Section: Optical Flow Field Computations and Use (H)
Optical Flow, Parallel
Section: Optical Flow Field Computations and Use (H)
Section: Parallel Optic Flow Computation, Efficient Computation (H2)
Optical Flow, Regions
Section: Optical Flow -- Matching Using Areas (H2)
Section: Optical Flow Field Computations and Use (H)
Optical Flow, Smoothing
Section: Optical Flow Field -- Smoothness (H1)
Section: Optical Flow Field Computations and Use (H)
Optical Flow, Translation
Section: Optical Flow Field Computations and Use (H)
Section: Optical Flow for Simple Motions (H2)
Optical Interferometry
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Optical Interferometry, Moire Patterns (H2)
Optical Tomography
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Optical Tomography, Infrared Tomography (H2)
Optics
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Optical Filtering (H2)
Optimal Path Forest
Section: Optimal Path Forest Classification (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Optimization Techniques
Section: Evidence Theory, Combination Techniques, Optimization Techniques (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Optimization
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Optimizations, Computational Issues (H3)
Optoacoustic Tomography
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Photoacoustic Tomography, Ultrasonic, Generation (H2)
Orbit
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Orbit Determination (H2)
Orchards
Section: Apple Trees, Plantations, Analysis, Diseases (H4)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Citrus Trees, Orchards, Diseases (H4)
Section: Coffee Trees, Trees as Crops, Tea Trees (H4)
Section: Olive Trees, Orchards, Diseases (H4)
Section: Orchards, Plantations, Trees as Crops (H3)
Section: Palm Trees, Oil Palms, Trees as Crops (H4)
Section: Rubber Trees, Plantations, Analysis (H4)
8 for Orchards
Order Statistics
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Order Statistics, Rank Statistics, Filters (H3)
Organic Carbon
Section: Organic Carbon, Dissolved Organic Matter, Water Quality (H3)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Soil Organic Carbon (H2)
Orientated Objects
Section: ATR - Oriented Objects, Vehicles, Aerial Images (H3)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Orientation
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: ATR - Oriented Objects, Vehicles, Aerial Images (H3)
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Oriented Texture, Directional Texture Patterns (H2)
Orientation, Camera
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Camera Orientation Computations, Camera Calibration, Interior Orientation, Exterior Orientation (H2)
Oriented Texture
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Oriented Texture, Directional Texture Patterns (H2)
Orthogonal Views
Section: Representations from Orthogonal, Orghographic or Multiple Views (H2)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Orthographic Views
Section: Representations from Orthogonal, Orghographic or Multiple Views (H2)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Orthoimage
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Orthoimage Generation, Analysis, DEM (H2)
* Mosaicking of Orthorectified Aerial Images
Orthophotography
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Orthoimage Generation, Analysis, DEM (H2)
Orthorectification
Section: Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR (H)
Section: Orthoimage Generation, Analysis, DEM (H2)
Out-of-Distribution
Section: Outlier Detection and Analysis, Robust Analysis, Out of Distribution (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Outgoing Longwave Radiation
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Section: Upward Longwave Radiation, Outgoing Longwave Radiation, Upwelling Radiation (H4)
Outgoing Shortwave Radiation
Section: Net Radiation, Surface Shortwave Net Radiation, Outgoing Shortwave, Radiation Budget (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)
Outliers
Section: Outlier Detection and Analysis, Robust Analysis, Out of Distribution (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Outpainting
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Outpainting, Extrapolation (H4)
Ovarian Cancer
Section: Medical Applications -- Cervical Cancer Analysis, Ovarian Cancer (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Overfitting
Section: Network Overfitting (H4)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Overhead Traffic
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Traffic Surveillance, Analysis, Aerial Images, Overhead, Airborne Sensors (H4)
Overtaking
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Overtaking Analysis, Control (H4)
Overviews
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: General Group Overview Papers (H1)
Ownership Protection
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Watermarks for Copyright, Ownership Protection, Authentication, Verification (H2)
Ozone
Section: Pollution, Ozone Measurements, O3 (H4)
Section: Remote Sensing General Issue, Land Use, Land Cover (H)