Keywords r

Radar Section: ATR -- Model, Object Based Radar and SAR Recognition (H3)
Section: ATR -- Radar, SAR Applications (H2)
Section: Borehole Radar, Analysis, Applications (H3)
Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Doppler Radar Applications (H3)
Section: Fusion, Radar Data, SAR Data (H3)
Section: Ground Penetrating Radar, Buried Objects, UXO, Landmines (H3)
Section: Moving Targets, Radar, SAR Applications (H3)
Section: Power Line Extraction, Radar, SAR, Lidar, Laser, Depth (H2)
Section: Radar for Land Cover, SAR for Land Cover, Remote Sensing (H3)
Section: Radar, Extraction of Features, Segmentation (H2)
Section: Radar, SAR Analysis (H1)
Section: Radar, SAR, Autofocus, Focus (H2)
Section: Radar, SAR, Microwave Scattering Models (H2)
Section: Radar, Speckle Analysis and Removal, Speckle Reduction, Despeckle (H2)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Through the Wall Imaging, Radar, Microwave Imaging (H4)
Section: Tunnels, Tunnel Descriptions, Tunnel Analysis (H2)
Section: Weather Radar Applications (H3)
Section: Wind Sensing, Wind from Sensors (H3)
* Remote Sensing with Imaging Radar
22 for Radar

Radar, Roads Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: Road Extraction in Radar, SAR, Lidar, Laser, Depth (H2)

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

Radiance Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Light Source Direction Computations, Illumination Information, Illuminant (H3)

Radiography Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: X-Ray Images, Radiography (H1)

Radiometric Calibration Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Destriping Images, Pushbroom, Scanner, Remote Sensing Imagry (H3)
Section: Photometric Calibration, Radiometric Calibration, Color Calibration (H2)
Section: Radiometric Calibration of Remote Sensing, Satellite and Space Images (H3)
Section: White Balance, Automatic White Balance (H3)

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

Radon Transform Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Transforms, Radon, Haar, Hadamard, etc. (H2)

Rail Traffic Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Rail Traffic Controls, Trains (H4)

Railroad Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Rail Traffic Controls, Trains (H4)

Railroads Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Railroads, Inspection, Obstacles (H3)

Rainfall Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: Rainfall Analysis, Rain, Precipitation, Weather Radar (H3)

Ramp Controls Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Ramp Controls, Highway Traffic Control (H4)

Random Field Model Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Random Field Models for Structure Matching (H3)

Random Forest Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Random Forests Classification (H3)

Range Data Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Range Data Super Resolution, Depth Super Resolution (H3)

Range Data, Registration Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Artificial Vision for Mobile Robots: Stereo Vision and Multisensory Perception
* Autonomous Navigation in Cross-Country Terrain
* High-Resolution Terrain Map from Multiple Sensor Data
* Rigid Body Motion from Range Image Sequences
7 for Range Data, Registration

Range Images Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Hough-transform detection of lines in 3-space
* Resolving View Sensitivity With Surface Locality

Range Matching Section: Registration or Multiple Range Images, Range Image Registration (H4)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)

Range Segmentation Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Range and Color, RGB-D Segmentation and Analysis (H3)
Section: Region Techniques for Range and Surfaces (H2)

Range Sensor Section: Acoustic, Sonar Sensors for Range, Underwater Acoustic Sensing (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Depth, Range Sensors for Machine Vision (H2)
Section: Laser Sensors for Range, Time of Flight (H3)
Section: Stereo Sensors for Range (H2)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)

Range Section: Fusion, Range or Depth and Intensity or Color Data (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)

Range, Edges Section: Computation of Edges in Range, Depth or Multi-Dimensional Data (H1)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)

Rangeland Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: Pasture, Grassland, Rangeland Analysis and Change (H3)

Rank Statistics Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Order Statistics, Rank Statistics, Filters (H3)

RANSAC Section: General References for Matching (H1)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* IMPSAC: Synthesis of Importance Sampling and Random Sample Consensus
* Minimal Subset Random Sampling for Pose Determination and Refinement
* Model Fitting with Sufficient Random Sample Coverage
* Performance Evaluation of RANSAC Family
* Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography
8 for RANSAC

Rare Event Section: Detecting Anomalies, Abnormal Event, Abnormal Behavior, or Rare Events, Rare Behaviors (H3)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)

Rasterization Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Line Vectorization, Document Analysis (H2)

Rate-Control Section: General Rate-Distortion Tradeoff Issues, Single Images (H3)
Section: High Efficiency Video Coding, HEVC Rate Control Issues (H4)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: MPEG Rate-Distortion Trade-Offs, Transmissions Issues (H3)

Rate-Distortion Section: General Rate-Distortion Tradeoff Issues, Single Images (H3)
Section: General Rate-Quality, Rate Distortion, Rate Control, Error Tradeoffs for Video (H3)
Section: High Efficiency Video Coding, HEVC Rate Control Issues (H4)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: MPEG Rate-Distortion Trade-Offs, Transmissions Issues (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)
7 for Rate-Distortion

Rate Control Section: General Rate-Quality, Rate Distortion, Rate Control, Error Tradeoffs for Video (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
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)

Rational Function Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Rational Function Models, Rational Polynomial Coefficients, Camera Specification (H3)

Rational Polynomial Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Rational Function Models, Rational Polynomial Coefficients, Camera Specification (H3)

RBG-D Section: Human Detection, People Detection, Pedestrians, Using Depth, Stereo (H4)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)

Re-Identification Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Re-Identification using Color Features (H4)
Section: Tracking People Across Disjoint Views (H4)
Section: Tracking People with Multiple Cameras, Stereo, or Depth (H4)
Section: Tracking People, Re-Identification Issues, Occlusions (H4)
Section: Tracking Several People, Occlusions (H4)

Reactive Illumination Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Projector-Camera Systems, Camera-Projector Systems, Projection onto Surface (H3)

Real-Time Edges Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Edge Detection, Computation Techniques for Speed (H3)

Real-Time Optical Flow Section: Optical Flow Field Computations and Use (H)
Section: Real-Time Computation, Real-Time Implementation, Hardware for Optical Flow (H1)

Real-Time System Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* W4: Real-Time Surveillance of People and Their Activities

Real-Time Systems Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Multiple Target Localisation at over 100 Fps
* Robust feature matching in 2.3µs

Real-Time Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Real-Time Motion Segmentation, Hardware for Motion Detection (H3)

Real Time Tracking 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)

Real Time Vision Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Agriculture, Inspection -- Animals, Animal Detection (H4)
Section: Agriculture, Inspection -- Fish, Fish Motion, Detection (H4)
Section: Agriculture, Inspection -- Food Products, Plants, Farms (H3)
Section: Agriculture, Inspection -- Meat (H4)
Section: Combined Audio Visual Recognition and Analysis (H3)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Gesture Recognition Techniques (H2)
Section: Head Motion, Head Tracking, Tracking Faces in Video (H1)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Industrial Applications (H1)
Section: Inspection -- Chips, Wafers, PCB, PWB, VLSI, IC, Disks, etc. (H3)
Section: Inspection -- Defect Detection, Crack Detection (H3)
Section: Inspection -- Lumber, Logs, Wood (H3)
Section: Inspection -- Metal Inspection, Castings, Machining (H3)
Section: Inspection -- Paint and Printing Quality, Print Analysis (H3)
Section: Inspection -- Solder Joints, Welding, Pipes (H3)
Section: Inspection -- Textiles, Fabrics, Fibers (H3)
Section: Inspection Systems and Techniques (H2)
Section: Lipreading, Lip Reading, Lip Tracking (H2)
Section: Other Industrial Applications Areas (H2)
Section: Tracking Faces, Heads Using Color Models (H3)
Section: Video Conferencing, Videoconference, Teleconference (H2)
* Designing a Deer Detection System Using a Multistage Classification Approach
24 for Real Time Vision

Real Time, Hough Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Real-Time Processor for the Hough Transform, A

Real Time, Stereo Section: Stereo: Real Time Systems, Graphical Processing Units, GPU Implementations (H2)
Section: Stereo: Real Time Systems, Hardware Implementations (H1)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)

Recognition by Function Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Object Recognition by Functional Parts

Recognition by Parts Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Appropriate-Scale Local Centers: A Foundation for Parts-Based Recognition

Recognition Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Support Vector Machines, SVM, Applied to Recognition (H3)
Section: Support Vector Machines, SVM, Incremental, Multi-Step (H3)
Section: Target Recognition with Tracking, Recognition in Sequences (H2)
Section: Training Support Vector Machines, SVM Training, Learning (H3)
* Geometric Feature Detection for Reverse Engineering Using Range Imaging
* Parallel Optical-Feature Extraction by Use of Rotationally Multiplexed Holograms
* Representation and Recognition of Three-Dimensional Shapes
10 for Recognition

Recognition, ATR Section: ATR Applications, Automatic Target Recognition (H1)
Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)

Recognition, Context Based Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Context-Based Vision: Recognition of Natural Scenes

Recognition, Indexing Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Complete and Extendable Approach to Visual Recognition, A
* TOSS: A System for Efficient Three Dimensional Object Recognition

Recognition, Model Based Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: 3-D Object Recognition Using Invariants (H2)
Section: ACRONYM and SUCCESSOR Papers - Stanford University and Others (H2)
Section: Aspect Graph Matching, Characteristic Views (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Constraint Based Matching (H2)
Section: Context in Computer Vision (H2)
Section: Knowledge-Based Vision (H1)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Model Based Recognition Systems (H2)
Section: Recognition by Function (H2)
Section: Three-Dimensional Matching Using Hashing/Indexing (H2)
Section: University of Massachusetts VISIONS System (H2)
* Constructing Constraint Tables for Model-Based Recognition and Localization
* Perceptual Organization and Visual Recognition
15 for Recognition, Model Bas

Recognition, Systems Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Model Based Recognition Systems (H2)

Recognition, Techniques Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Recognition Systems Applied to Specific Applications (H1)

Recognition, Using Shape Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Model-based Shape from Contour and Point Patterns

Recognize Aerial Images Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Knowledge-Based System for Recognizing Man-Made Objects in Aerial Images, A
* Rule Based Interpretation of Aerial Imagery
* Structural Analysis of Complex Aerial Photographs

Recognize Aircraft * 3-Dimensional Aircraft Recognition Using Fourier Descriptors
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Aircraft Identification by Moment Invariants
* Constraint-Based System for Interpretation of Aerial Imagery, A

Recognize Airports Section: Airport Analysis Systems, Runways (H1)
Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)

Recognize Apples Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Automatic Apples Detection for an Agricultural Robot

Recognize Blocks World Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Scene Analysis Using Regions

Recognize Buildings Section: Building Analysis and Detection Systems, Multi-View (H1)
Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: CMU Building Systems (H2)
Section: KU Leuven Building Systems (H2)
Section: UMass Building Extraction Systems (H2)
Section: USC Building Systems (H2)

Recognize Characters Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Fourier Preprocessing for Hand Print Character Recognition
* IBM 1975 Optical Page Reader, Part II: Video Thresholding, The

Recognize Color Objects Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Data and Model-Driven Selection Using Color Regions
* Indexing Via Color Histograms

Recognize Cursive Script Section: Handwriting, Cursive Script Recognition Systems (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Multi-Level Perception Approach to Reading Cursive Script, A
* Reading Cursive Handwriting by Alignment of Letter Prototypes

Recognize Curved Objects Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Structured Description of Complex Objects

Recognize Drainage Networks Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* Automatic Inference of Elevation and Drainage Models from a Satellite Image
* Extraction of Drainage Networks from Digital Elevation Data, The

Recognize Faces Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Recognition and Analysis of Faces (H1)
* Classification of Facial Features for Recognition
* Locating Human Faces in Newspaper Photographs
* Visual Identification of People by Computer

Recognize General Objects 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)
* Parallel Recognition of Objects Comprised of Pure Structure
* Recognizing Unexpected Objects: A Proposed Approach
* Vision Constraint Recognition System: Analysing the Role of Reasoning in High Level Vision, The

Recognize Hands Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Inference of Structure: Hands

Recognize Handwriting Section: Handwriting, Cursive Script Recognition Systems (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: On-Line Cursive Script Recognition Systems (H4)
* Machine Recognition of Hand Printing
* On-Line and Off-Line Handwriting Recognition: A Comprehensive Survey

Recognize Line Models Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (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: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Approach to the Recognition of Contours and Line-Shaped Objects, An
* Iterative Hough Procedure for Three-Dimensional Object Recognition, An
* Line-Drawing Interpretation: A Mathematical Framework
* Machine Perception of 3-D Solids
* Recognition of Polyhedra from Range Data
9 for Recognize Line Models

Recognize Objects - Hierarchical Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Hierarchical Object Recognition Using Libraries of Parameterized Model Sub-Parts

Recognize Range Data 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)
* Evidence-Based 3D Vision System for Range Images, An
* Recent Progress in the Recognition of Objects from Range Data
* Representation and Recognition of Objects from Depth Maps

Recognize Roads Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: Road Following, Road Tracking Systems, Connecting Fragments, Extracting Fragments (H2)
Section: Road Network Detection, Road Extraction Systems (H1)
* Computer Recognition of Roads from Satellite Pictures
* Representation and Recognition of Elongated Regions in Aerial Images
* SRI Road Expert: Image-to-Database Correspondence, The

Recognize Schematic drawings Section: OCR, Document Analysis and Character Recognition Systems (H)
* DRACAP: Drawing Capture for Electronic Schematics

Recognize Structures Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Image Registration by Matching Relational Structures
* Some Techniques for Recognizing Structures in Pictures

Recognize Symbols Section: OCR, Document Analysis and Character Recognition Systems (H)
* Automatic Circuit Diagram Reader with Loop-Structure-Based Symbol Recognition, An

Recognize Three-Dimensional Objects * 3-D Object Recognition Using Surface Descriptions
* 3-D Recognition and Positing Algorithm Using Geometrical Matching Between Primitive Surfaces, A
* 3D Object Recognition Via Simulated Particles Diffusion
* 3D Objects Recognition by Optimal Matching Search of Multinary Relations Graphs
* 3D-POLY: A Robot Vision System for Recognizing Objects in Occluded Environments
* 3D-Profile Method for Object Recognition, The
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: 3-D Object Recognition from Pose Estimation or Alignment (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (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)
* ATN Model for 3D Recognition of Solids in Single Views, An
* Cross-Angle Transform for Viewer-Independent Recognition of 3-D Objects
* Determining Linear Shape Change: Towards Automatic Generation of Object Recognition Programs
* Estimating and Recognizing Parameterized 3-D Objects Using a Moving Camera
* Experiments in Intensity Guided Range Sensing Recognition of Three-Dimensional Objects
* Intrinsic and Extrinsic Surface Characteristics
* Model Based Vision System for Recognition of Machine Parts, A
* Model-Based Recognition Using 3D Shape Alone
* Modeling Sensor Detectability and Reliability for Model-Based Vision
* Object Recognition and Localization via Pose Clustering
* Object Recognition Using Three-Dimensional Information
* On Shapes
* On the Recognition of Curved Objects
* Precompiling a Geometric Model into an Interpretation Tree for Object Recognition in Bin-Picking Tasks
* Range Image Understanding
* Recognition and Positioning of Three-Dimensional Objects by Combining Matchings of Primitive Local Patterns
* Robotic Object Recognition Using Vision and Touch
* Special Purpose Automatic Programming for 3D Model-Based Vision
* Using Surfaces and Object Models to Recognize Partially Obscured Objects
* Visual Recognition from Spatial Correspondence and Perceptual Organization
32 for Recognize Three-Dimensional Objects

Recognize Three-Dimensional Surfaces Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Model-Based Recognition and Localization from Sparse Range or Tactile Data

Recognize Two-Dimensional Objects * 2-D Object Recognition Using Hierarchical Boundary Segments
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (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)
* Combinatorics of Object Recognition in Cluttered Environments Using Constrained Search, The
* Computer Recognition of Partial Views of Three Dimensional Curved Objects
* Computer Vision Algorithms Used in Recognition of Occluded Objects
* GROPER: A Grouping Based Recognition System for Two Dimensional Objects
* Model Based Vision System to Identify and Locate Partially Visible Industrial Parts, A
* New Measures of Similarity between Two Contours Based on Optimal Bivariate Transforms
* On Recognition of 3-D Objects from 2-D Images
* Planning A Strategy for Recognizing Partially Occluded Parts
* Recognition of Object Families Using Parameterized Models
* Recognition of Occluded Shapes Using Relaxation
* Recognition of Occluded Two Dimensional Objects
* Recognition of Two-Dimensional Objects Using Hypothesis Integration Techniques
* Recognizing and Locating Partially Visible Workpieces: The Local-Feature-Focus Method
* Recognizing Partially Occluded Parts
* Shape Recognition from Single Silhouettes
* Silhouette-Slice Theorems
* Two-Dimensional Object Recognition Using Multiresolution Models
21 for Recognize Two-Dimensional Objects

Recommender Systems Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Movie, Video Recommender Systems, Personalization, Video on Demand (H3)

Reconfigurable Mesh 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: Reconfigurable Mesh Architectures and Algorithms (H3)
* Building a Quadtree and Its Applications on a Reconfigurable Mesh

Reconstruction from Range Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: General Reconstructions (H2)

Reconstruction 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: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Electrical Impedance Tomography, EIT (H2)
Section: Few Views, Limited Views, Low Dose, Tomographic Image Reconstruction (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Image Reconstruction (H2)
Section: Kidney Disease, Tomography, CAT Analysis, Other Methods (H3)
Section: Liver Disease, Tomography, CAT Analysis (H3)
Section: Lossless, Reconstructions from Wavelet Coded Images (H4)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Reconstruction from Coded Images, Error Recovery (H3)
Section: Statistical, Bayesian Tomographic Image Reconstruction (H3)
Section: Surveys, Overviews, Evaluations and Analysis of 3-D Reconstructions (H2)
Section: Tomographic Image Generation, CAT, CT, Reconstruction (H2)
Section: Tomographic Object Construction, Object Extraction, Analysis, Organs (H2)
* Robust and Efficient Fourier-Mellin Transform Approximations for Gray-Level Image Reconstruction and Complete Invariant Description
17 for Reconstruction

Reconstruction, 3-D Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Surveys, Overviews, Evaluations and Analysis of 3-D Reconstructions (H2)

Reconstruction, Multi-Grid Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Surfaces, Hierarchical Reconstruction, Multi-Grid Reconstruction Approaches (H2)

Rectification Section: Image Manipulation -- Rectification (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)

Redeye Detection Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Redeye Detection, Red Eye Detection (H4)

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

Reflectance Map Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Albedo, Reflectance Map from Multiple Images (H2)

Reflectance Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Reflectance Computations, Albedo (H2)
Section: Reflections and Color Models, Reflectance (H3)

Reflections Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Interreflections, Reflections (H2)

Refraction Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Refraction, Refractive Geometry (H2)

Refractive Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Refractive, Water, Underwater Camera Calibration (H3)

Region Coding Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Using Arbitrary Region Coding (H4)

Region Extraction Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Extraction and Analysis of Connected Components and Boundaries (H1)

Region Growing Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Segmentation by Region Growing Techniques (H1)
Section: Superpixel Region Growing (H2)
* Region Competition and its Analysis: A Unified Theory for Image Segmentation
* Spatiotemporal Segmentation Based on Region Merging

Region Matching Section: Computation and Matching for Region Coding (H4)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Region Properties for Matching (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)

Region of Interest Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Region of Interest Detection, ROI (H2)

Region Operations, Quadtree Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Quadtree Generation and Computations (H2)

Region Tracking Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Region, Object, Target Tracking (H2)

Regions and Edges Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* New Approach of Color Images Segmentation Based on Fusing Region and Edge Segmentations Outputs, A

Regions Section: Stereo Analysis: Regions, Combine Area and Edge (H2)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)

Registration Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Brain, Cortex, Registration, Alignment, MRI, Other (H3)
Section: Building Change Detection (H4)
Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: Change Detection for Damage Assessment (H3)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Face Alignment, Registration, Recognition, 3-D Models (H4)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Image Copy, Duplicate Image Detection (H4)
Section: Image Registration Techniques (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Register 3-D Data, Range Registration, 3-D Correspondence (H3)
Section: Register 3-D LIDAR Data, Profiles (H4)
Section: Register 3-D Surfaces, Mesh Models (H4)
Section: Register Point Cloud Data, Point Cloud Matching, Laser Scanner Data (H4)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Site Model Change Detection, Map Update (H3)
Section: Site Model Registration, Georeference, Geo-Registeration (H2)
Section: Video Copy, Video Duplicate Detection (H4)
Section: Video Registration Techniques, Synchronizing, Synchronization (H3)
* Evaluation of Ridge Seeking Operators for Multimodality Medical Image Matching
* Registration and Exploitation of Multi-pass Airborne Synthetic Aperture Radar Images
* Robotic System for 3-D Model Acquisition from Multiple Range Images, A
23 for Registration

Registration, 3-D Section: Register 3-D Data, Range Registration, 3-D Correspondence (H3)
Section: Register 3-D LIDAR Data, Profiles (H4)
Section: Register 3-D Surfaces, Mesh Models (H4)
Section: Register Point Cloud Data, Point Cloud Matching, Laser Scanner Data (H4)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Surface Matching, Deformable Surface Matching (H2)

Registration, Range Section: Range Data Matching -- Accumulation Methods (H3)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Surfaces and Range Data Matching (H2)

Registration, Ultrasound Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Surface Registration, Sonar, Ultrasound, Acoustic (H4)

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

Regularization Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Optical Flow Field Computations and Use (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Regularization Theory and Practice (H1)
* Discontinuity-Preserving and Viewpoint Invariant Reconstruction of Visible Surfaces Using a First-Order Regularization
* Edge detection with iteratively refined regularization
* Fast Scalable Algorithm for Discontinuous Optical-Flow Estimation, A
* Machine Learning, Machine Vision, and the Brain
* Motion Computation and Interpretation Framework for Oceanographic Satellite Images, A
* Regularization of Discontinuous Flow Fields
* Robust Estimation of 3-D Motion Parameters from a Sequence of Image Frames Using Regularization
* Spatial and Temporal Surface Interpolation Using Wavelet Bases
* Spatial-Resolution Properties of Penalized Likelihood Image Reconstruction: Space Invariant Tomographs
17 for Regularization

Rehabilitation Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Rehabilitation Systems, Rehabilitation Techniques (H4)

Relational Descriptions Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Basic Comparison of Relational Network Descriptions (H2)
Section: Descriptions Based on Relational Network Structures (H1)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)

Relational Distance Section: Basic Comparison of Relational Network Descriptions (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)

Relaxation 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: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (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: Improving Edges by Neighborhood Processing, Relaxation, Multi-Scale (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Optical Flow Field Computations and Use (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: Segmentation by Thresholding, Quantization, or Relaxation (H2)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* Bit-vector Algorithms for Binary Constraint Satisfaction and Subgraph Isomorphism
* Comparison of Some Segmentation Algorithms for Cytology, A
* Computational Techniques in the Visual Segmentation of Static Scenes
* Computer Vision Based on a Hypothesization and Verification Scheme by Parallel Relaxation
* Computing Correspondences in a Sequence of Non-Rigid Objects
* Decision Theory and Artificial Intelligence: I. A Semantics Based Region Analyzer
* Detection of Binocular Disparities
* Extracting and Labeling Boundary Segments in Natural Scenes
* Finding Range From Stereo Images
* Finding the Parts of Objects in Range Images
* Image Analysis Using Multigrid Relaxation Methods
* Interpretation of Visual Motion, The
* Iterative Enhancement of Noisy Images
* Learning Compatibility Coefficients for Relaxation Labeling Processes
* Matching Linear Features of Images and Maps
* Multi-Resolution Relaxation
* Multigrid Bayesian Estimation of Image Motion Fields Using Stochastic Relaxation
* Parallel Architecture for Probabilistic Relaxation Operations on Images, A
* Parallel Binocular Stereo Algorithm Utilizing Dynamic Programming and Relaxation Labelling, A
* Perceptual Segmentation of Nonhomogeneous Dot Patterns
* Point Pattern Matching by Relaxation
* Recognition of Occluded Shapes Using Relaxation
* Recognition of Occluded Two Dimensional Objects
* Region Growing in Textured Outdoor Scenes
* Registering Landsat Images by Point Matching
* Relational Matching with Stochastic Optimisation
* Relaxation Methods in Multispectral Pixel Classification
* Role of Constraints and Discontinuities in Visible Surface Reconstruction, The
* Scene Analysis Using a Semantic Base for Region Growing
* Segmentation of FLIR Images: A Comparative Study
* Shape from Patterns: Regularization
* Shape Matching Using Relaxation Techniques
* Simple Parallel Hierarchical and Relaxation Algorithms for Segmenting Noncausal Markovian Random Fields
* Some Experiments in Relaxation Image Matching Using Corner Features
* Temporal Constraints for Estimating Optic Flow
* Toward Discrete Geometric Models for Early Vision
* Unsupervised Textured Image Segmentation Using Feature Smoothing and Probabilistic Relaxation Techniques
* Volumetric Model and 3D Trajectory of a Moving Car from Monocular TV Frames Sequence of a Street Scene
53 for Relaxation

Relaxation, Continuous Section: Continuous Relaxation Theory, Constraint Satisfaction (H3)
Section: Faugeras and Berthod Gradient Optimization Methods (H3)
Section: Graph Matching, Continuous Relaxation, Constraint Satisfaction (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)

Relaxation, Discrete Section: Discrete Relaxation Methods (H2)
Section: Discrete Relaxation Theoretical Issues (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Consistency Technique for Pattern Association, A

Relaxation, Early work Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Scene Labeling by Relaxation Operations

Relaxation, Edges Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Computational Techniques in the Visual Segmentation of Static Scenes

Relaxation, Evaluation Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Algorithms for Inexact Matching
* Note on the Evaluation of Probabilistic Labelings, A
* Relaxation Matching Techniques: A Comparison

Relaxation, Matching * 3-D Object Recognition Using Bipartite Matching Embedded in Discrete Relaxation
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Relaxation Based Techniques (H3)

Relaxation, Results Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Disparity Analysis of Images
* Semantic Description of Aerial Images Using Stochastic Labeling

Relaxation, Survey Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Algorithms for Constraint-Satisfaction Problems: A Survey
* Cooperating Processes for Low-Level Vision: A Survey
* Iterative Methods in Image Analysis
* Relaxation Labelling Algorithms: A Review

Relaxation, Theory Section: Hummel and Zucker Relaxation Papers (H3)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Shmuel Peleg Theoretical Relaxation Papers (H3)
* On the Foundations of Relaxation Labeling Processes
* Scene Labeling: An Optimization Approach

Relevance Feedback Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Relevance Feedback, Tsinghua Univ. and Related Papers (H4)
Section: User Interaction, Relevance Feedback, External Information (H3)

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

Remeshing Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Mesh Representations, Remeshing Algorithms (H4)

Remote Sensing * *Earth Observation and Remote Sensing
* *Earth Observation Magazine
* *Image and Signal Processing for Remote Sensing III
* *International Annals of Photogrammetry and Remote Sensing
* *International Archives of Photogrammetry and Remote Sensing
* *International Journal of Remote Sensing
* *ISPRS Journal of Photogrammetry and Remote Sensing
* *Photogrammetric Engineering and Remote Sensing
* *Remote Sensing of Environment
Section: Analysis of Maps, Vision, Image Analysis (H3)
Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Building Analysis and Detection Systems, Multi-View (H1)
Section: Building Change Detection (H4)
Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: Change Detection for Damage Assessment (H3)
Section: Classification for Crops, Analysis of Production, Specific Crops, Specific Plants (H3)
Section: Classification for Urban Area Land Cover, Remote Sensing (H3)
Section: CMU Building Systems (H2)
Section: CMU MAPS Image Database System (H1)
Section: Disaster Management, Damage Mitigation, Emergency Management (H4)
Section: Evapotranspiration, Evaporation, Remote Sensing (H3)
Section: General Cartography Issues (H1)
Section: General Site Model Use, Program Surveys (H1)
Section: Global-Scale Analysis, Global Land Cover Analysis (H3)
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: KU Leuven Building Systems (H2)
Section: Land Cover Change Analysis, Remote Sensing Change Analysis, Temporal Analysis (H3)
Section: Land Cover, Land Use, General Problems, Remote Sensing (H3)
Section: Landslide Analysis, Damage Assessment, Deformations (H4)
Section: Lidar for Land Cover, Laser Scanners for Land Cover, Remote Sensing (H3)
Section: Map Analysis, Analysis of Map data, Map Processing (H2)
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Other Soil Properties, Remote Sensing (H3)
Section: Pansharpening, Fusion of Aerial Images (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Radar for Land Cover, SAR for Land Cover, Remote Sensing (H3)
Section: Recognition Systems Applied to Specific Applications (H1)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Remote Sensing Issues, Applications (H2)
Section: Remote Sensing Issues, Evaluations of Techniques, Validation (H2)
Section: Road Following, Road Tracking Systems, Connecting Fragments, Extracting Fragments (H2)
Section: Road Network Detection, Road Extraction Systems (H1)
Section: Road Network Model Integration, Updating, and Change Detection (H2)
Section: Site Model Change Detection, Map Update (H3)
Section: Site Model Construction and Evaluation, General Mapping (H2)
Section: Site Model Registration, Georeference, Geo-Registeration (H2)
Section: Soil Moisture, Remote Sensing (H3)
Section: SRI General Cartography Systems (H1)
Section: Surface Temperature, Atmospheric Measurements, Remote Sensing (H3)
Section: UMass Building Extraction Systems (H2)
Section: USC Building Systems (H2)
* Active Fusion: A New Method Applied to Remote Sensing Image Interpretation
* Classification of Croplands Through Integration of Remote-Sensing, GIS, and Historical Database
* Correlation Techniques and Devices
* Digital Image Processing of Remotely Sensed Data
* Experimental Comparison of Neural and Statistical Nonparametric Algorithms for Supervised Classification of Remote Sensing Images, An
* Fuzzy-Logic and Neural Techniques Integration: An Application to Remotely-Sensed Data
* Numeric and Symbolic Data Fusion: A Soft Computing Approach to Remote Sensing Images Analysis
60 for Remote Sensing

Rendering Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Computer Graphics, Rendering Issues (H3)
Section: Data Visualization (H4)
Section: GPU Implementations of Rendering, Hardware Implementations (H4)
Section: Graphics, Rendering Issues Related to Artistic Interpretation (H4)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Rendering Specific Surfaces, Applied Rendering (H4)
Section: Rendering, Cloth, Clothing, Fabric (H4)
Section: Texture Mapping, Terrain Visualization, Terrain Rendering, DEM Rendering (H4)
Section: Virtual View Generation, View Synthesis, Image Based Rendering, IBR, Morphing (H2)
* Disparity field and depth map coding for multiview 3D image generation
11 for Rendering

Replicator Equations Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Replicator Equations, Maximal Cliques, and Graph Isomorphism

Representation by Parts Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Representation of Parts, Part-Based Models (H1)

Representation Section: Books, Collections, Overviews, General, and Surveys (H)
Section: Geometry of Visual Space (H3)
Section: Image Databases, Large Scale Systems, Web-Scale System (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Role of Representation in Vision (H3)
Section: System Issues, Data Structures (H3)

Representation, 2D Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Two Dimensional Data Representations, Image Order (H1)
* Coding of Two-Tone Images

Representation, Chain Codes Section: Chain Code Representations (H3)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)

Representation, Contour Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: General Contour Representations (H3)

Representation, Curves Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Shape Description by Time Series

Representation, Fractals Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Fractal Representations, Fractal Dimension (H2)

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

Representation, Log Mapping Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Complex Log Mapping, Algorithms and Sensors (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Geometric invariance in space-variant vision systems: The exponential chirp transform

Representation, Parts -- 3D Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Representation of Parts, Part-Based Models (H1)

Representation, Polygon Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: General Polygonal Representations and Computations (H3)

Representation, Pyramid 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)
Section: Pyramid Representations (H2)
* L-(2) Polynomial Spline Pyramid, The
* Pyramid Framework for Early Vision: Multiresolution Computer Vision, A
* Smart Sensing in Machine Vision

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

Representation, Runlength Code Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Run-Length Coding Representations and Operations (H2)

Representation, Scale-Space Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Discrete Scale-Space Theory and the Scale-Space Primal Sketch
* Scale-Space Theory in Computer Vision

Representation, Superquadric Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: SuperQuadric Representations (H1)

Representation, Wavelets Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Using Wavelets for Detection, Recognition, Fusion (H3)
Section: Wavelet Representations (H2)
Section: Wavelets, Mallat Papers (H3)
Section: Wavelets, Surveys, Reviews, Overviews, Evaluations, General (H3)

Representation, Wavlets Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Wavelets for Curves and Surfaces (H3)

Reranking Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: Reranking in Query, Relevance Feedback (H4)

Research Group, Australia * *Adept Electronic Solutions
* *Australian Centre for Visual Technologies
* *Australian National University, The
* *Cooperative Research Center for Sensor Signal and Image Processing
* *CSIRO Mathematical and Information Sciences
* *Curtin University
* *Monash University
* *National ICT Australia
* *University of Adelaide, The
* *University of New South Wales
* *University of Technology, Sydney
* *University of Western Australia
* *University of Wollongogn
13 for Research Group, Australia

Research Group, Austria * *Austrian Institute of Technology
* *Graz University of Technology
* *Institute of Science and Technology
* *Joanneum Research
* *Johann Radon Institute for Computational and Applied Mathematics - RICAM
* *Technical University of Vienna

Research Group, Belarus * *Belarusian Academy of Sciences

Research Group, Belgium * *Ghent University
* *Katholieke University Leuven
* *Royal Military Academy
* *University of Liège

Research Group, Brazil * *Universidade Federal do Paraná
* *University of Sao Paulo

Research Group, Canada * *Carleton University
* *Concordia University
* *Laval University
* *McGill University
* *Queen's University
* *SANI International Technology Advisors Inc.
* *Simon Fraser University
* *Universite de Sherbrooke
* *University of Alberta
* *University of British Columbia
* *University of Calgary
* *University of Guelph
* *University of Ottawa
* *University of Saskatchewan
* *University of Toronto
* *University of Waterloo
* *University of Western Ontario
* *Université du Quebec
* *York University
19 for Research Group, Canada

Research Group, China * *Chinese Academy of Sciences, Institute of Automation
* *Lotus Hill Institute
* *Tsinghua University

Research Group, Company * *AccuSoft
* *ActivEye
* *Adept
* *Alpha Tec Ltd.
* *Amerinex Applied Imaging
* *Avaya Labs
* *Boston Dynamics
* *Charles River Analytics, Inc.
* *Cipherstone Technologies AB
* *Daimler
* *Definiens
* *Delphi Electronics and Safety
* *Digital Equipment Corp.
* *Disney Research
* *Epson Research and Development
* *GE Research
* *Gentec
* *Heartland Robotics
* *Honeywell
* *HP Labs
* *HRL Laboratories
* *IBM Journal of Research and Development
* *IBM Research
* *IBM Systems Journal
* *IBM T.J. Watson Research Center
* *IBM Technical Disclosure Bulletin
* *Imagen
* *Imagineer Systems
* *Intel Corp.
* *iRobot
* *KitWare, Inc
* *KritiKal Solutions
* *MERL: Mitsubishi Electric Research Laboratories
* *Microsoft Research
* *Migma Systems
* *Newton Labs
* *Palo Alto Research Center
* *Pattern Recogniton Company
* *Robot Vision 2 Inc.
* *Samsung Digital Media Solutions Lab
* *Sarnoff Research
* *Siemens VDO Automotive
* *SLR Engineering
* *Smith-Kettlewell Eye Research Institute
* *SRI AI Center
* *Utopia Compression
* *Videre Design
* *Virage
* *VisualSize
* *Willow Garage
Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
51 for Research Group, Company

Research Group, Costa Rica * *University of Costa Rica

Research Group, Croatia * *University of Zagreb

Research Group, Czech Republic * *Czech Technical University, Prague

Research Group, Denmark * *Aalborg University
* *IT University of Copenhagen
* *Technical University of Denmark
* *University of Copenhagen

Research Group, Europe * *3DTVS
* *ARTE
* *DrivSco Project
* *Euvision Technologies
* *Institute for the Protection and Security of the Citizen
* *MOBVIS
* *Pascal: Pattern Analysis, Statistical Modelling and Computational Learning
* *Toshiba Research Europe
8 for Research Group, Europe

Research Group, Finland * *Integrated Machine Vision Cluster
* *Lappeenranta University of Technology
* *University of Oulu

Research Group, France * *Ecole Centrale Paris
* *Eurecom
* *IMages Apprentissage GeometrIe Numerisation Environment
* *INRIA Grenoble Rhône-Alpes IMAG
* *INRIA Grenoble Rhône-Alpes
* *INRIA Lorraine
* *INRIA Sophia Antipolis
* *INRIA
* *INSA Lyon
* *IRISA/INRIA Rennes
* *ISIR - Institut des Systèmes Intelligents et de Robotique
* *Laboratoire d'informatique Gaspard-Monge
* *Laboratoire MATIS
* *MoDyPe: Modélisation de la dynamique pelvienne
* *RealViz
* *Sud Paris
* *Telecom Paris
* *Universite Paris IX Dauphine
* *University of Caen
* *University of Paris 13
* *Université de Bourgogne
* *Université Louis Pasteur, Strasbourg
22 for Research Group, France

Research Group, Germany * *Aachen University of Technology
* *Augmented Vision, DFKI
* *Berlin Technical University
* *Christian-Albrechts-University of Kiel
* *Deutsches Zentrum für Luft- und Raumfahrt e.V. (DLR)
* *DLR: German Aerospace Center
* *Dynamic Vision
* *Flying Eye
* *Fraunhofer Institute for Computer Graphics Multimedia Systems and Image Processing
* *Free University of Berlin
* *German Research Center for Artificial Intelligence
* *Goethe University Frankfurt
* *Heinrich Hertz Institut
* *Humboldt University Berlin
* *Karlsruhe Institute of Technology
* *Machine Vision Portal
* *Max Planck Center for Visual Computing and Communication
* *Max Planck Institute for Informatics
* *Ruhr-Universität Bochum
* *Saarland University
* *Technical University Munich, Remote Sensing Technology
* *Technical University Munich
* *Technical University of Darmstadt
* *Technische Universität München, Informatics, Robotic and Embedded Systems
* *Tübingen University
* *University of Bielefeld
* *University of Bonn, Computer Vision Group
* *University of Bonn, Institute for Photogrammetry
* *University of Bremen
* *University of Erlangen-Nuremberg
* *University of Freiburg
* *University of Hamburg
* *University of Hannover
* *University of Heidelberg BMCV
* *University of Heidelberg
* *University of Jena
* *University of Kaiserslautern, IUPR
* *University of Karlsruhe
* *University of Koblenz
* *University of Luebeck
* *University of Muenster
* *University of Paderborn
* *University of Stuttgart
43 for Research Group, Germany

Research Group, Greece * *Aristotle University of Thessaloniki
* *Democritus University of Thrace
* *Foundation for Research and Technology, Hellas
* *Fourth Institute of Computer Science
* *National Technical University of Athens

Research Group, Hong Kong * *Chinese University of Hong Kong, The
* *City University of Hong Kong
* *Hong Kong University of Science and Technology
* *University of Hong Kong

Research Group, Hungary * *Hungarian Academy of Sciences

Research Group, India * *Dhirubhai Ambani Institute of Information and Communication Technology
* *Indian Institute of Science, Bangalore
* *Indian Institute of Technology, Bombay
* *Indian Institute of Technology, Delhi

Research Group, Iran * *IPM Vision Group
* *K. N. Toosi University of Technology

Research Group, Ireland * *Dublin City University, Machine Vision Group
* *Dublin City University, Vision Systems Laboratory
* *Trinity College Dublin
* *University College Dublin

Research Group, Israel * *Ben-Gurion University of the Negev
* *Hebrew University
* *Technion Israel Institute of Technology
* *Tel Aviv University
* *Weizmann Institute of Science

Research Group, Italy * *Fondazione Bruno Kessler
* *Istituto Elettrotechnico Nazionale, IEN
* *Istituto Italiano di Tecnologia, IIT
* *Politecnico di Milano
* *SpotIt!
* *University of Bologna
* *University of Brescia
* *University of Florence
* *University of Genova
* *University of Messina
* *University of Milano
* *University of Modena and Reggio Emilia
* *University of Parma
* *University of Pavia
* *University of Pisa
* *University of Verona
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
17 for Research Group, Italy

Research Group, Japan * *Gunma University
* *Japan Advanced Institute of Science and Technology, JAIST
* *Keio University
* *Kumamoto University
* *Kyoto University
* *Kyushu University
* *Okayama University
* *OKI Electric Industry Company
* *Osaka University
* *Ritsumei University
* *Tokyo Institute of Technology
* *Toshiba
* *Tsukuba University
* *University of Tokyo
* *Waseda University
15 for Research Group, Japan

Research Group, Korea * *KAIST: Korean Advanced Institute of Science and Technology
* *Korea University
* *POSTECH: Pohang University of Science and Technology
* *Seoul National University
* *Sungkyunkwan University

Research Group, Mexico * *National University of Mexico

Research Group, New Zealand * *University of Auckland, The
* *University of Canterbury
* *University of Otago

Research Group, Norway * *Norwegian Color Research Laboratory
* *University of Bergen

Research Group, Portugal * *Instituto Superior Tecnico
* *Technical University of Lisbon
* *University of Algarve
* *University of Beira Interior

Research Group, Romania * *Technical University of Cluj-Napoca

Research Group, Singapore * *Nanyang Technological University
* *National University of Singapore

Research Group, Slovenia * *Mu Labs
* *University of Ljubljana

Research Group, South Africa * *University of Cape Town

Research Group, Spain * *Institute for Industrial Automation
* *Pompeu Fabra University
* *Rovira i Virgili University
* *Technical University of Catalonia
* *Universidad de Córdoba
* *Universidad de Las Palmas de Gran Canaria
* *Universidad Politechnica de Valencia
* *Universidad Rey Juan Carlos
* *Universitat de Girona
* *Universitat de València
* *University Jaume I
* *University of Alcala
* *University of Autononoma de Barcelona
* *University of Granada
* *University of Malaga
* *University of Politecnica Madrid
* *University of the Balearic Islands
17 for Research Group, Spain

Research Group, Sweden * *Halmstad University
* *Linkoping University
* *Lund University
* *Royal Institute of Technology KTH
* *Uppsala University

Research Group, Switzerland * *Ecole Polytechnique Fédérale de Lausanne
* *IDIAP
* *Swiss Federal Institute of Technology in Zurich
* *Swiss Federal Institute of Technology
* *University of Basel
* *University of Bern
* *University of Geneva
* *University of Lugano
8 for Research Group, Switzerland

Research Group, Taiwan * *Academia Sinica
* *National Taiwan Normal University

Research Group, The Netherlands * *Delft University of Technology
* *Eindhoven University of Technology
* *Erasmus University
* *inVISO
* *Tele Atlas N.V.
* *University of Amsterdam
* *University of Groninen
* *University of Leeuwarden
* *University of Twente
* *Utrecht University
10 for Research Group, The Netherlands

Research Group, Turkey * *Bilkent University
* *Bogaziçi University
* *Cankaya University
* *Koc University
* *Sabanci University

Research Group, UK * *BBC Research and Innovation
* *Birkbeck, University of London
* *Cambridge University
* *Cardiff University
* *Cranfield University
* *Heriot-Watt University
* *Imperial College, London
* *King's College London
* *Kingston University, London
* *Leeds University
* *Oxford Brookes University
* *Oxford
* *Queen Mary University of London
* *Queen's University of Belfast
* *Robert Gordon University
* *Scottish Imaging Network: SINAPSE
* *Sheffield Hallam University
* *Swansea University
* *University College London
* *University of Brighton
* *University of Bristol
* *University of Dundee
* *University of East Anglia
* *University of Edinburgh
* *University of Essex
* *University of Exeter
* *University of Glasgow
* *University of Manchester, Medicine
* *University of Manchester
* *University of Nottingham
* *University of of Bath
* *University of of Birmingham
* *University of Plymouth
* *University of Reading
* *University of Sheffield
* *University of Southampton
* *University of Surrey
* *University of Sussex
* *University of the West of England
* *University of Ulster
* *University of Warwick
* *University of York
42 for Research Group, UK

Research Group, US Government * *Electro Technical Laboratory
* *Jet Proplusion Laboratory
* *NIST Guide to Available Mathematical Software

Research Group, US * *Alcorn State
* *Arizona State University
* *Boston University
* *Brigham Young University
* *Brown University
* *California Institute of Technology
* *Carnegie Mellon Vision and Autonomous Systems Center, VASC
* *CCNY: City University New York
* *CITeR: Center for Identification Technology Research
* *CMU Digital Mapping Laboratory
* *CMU interACT
* *CMU Robotics Institute
* *CMU School of Computer Science
* *Colorado State University
* *Columbia University
* *Cornell University
* *Dartmouth University
* *Duke University
* *Fordham University
* *George Mason University
* *Georgia Tech
* *Harvard University
* *Hunter College of CUNY
* *International Computer Science Institute
* *Iowa State University
* *Johns Hopkins University
* *Lawrence Berkeley National Laboratory
* *Lehman College of CUNY
* *LookTel
* *Massachusetts Institute of Technology, AI Lab
* *Massachusetts Institute of Technology, Media Lab
* *Massachusetts Institute of Technology, Sensable City Laboratory
* *Massachusetts Institute of Technology
* *Michigan State University
* *Middlebury College
* *Naval Postgraduate School
* *New York University
* *North Carolina State University
* *Northwestern University
* *Numenta
* *Ohio State University
* *Oklahoma State University
* *Oregon State University
* *Penn State University
* *Princeton
* *Purdue University
* *Rensselaer Polytechnic Inst.
* *Rutgers
* *Stanford University Medical Center
* *Stanford University, Computer Science Departent
* *Stevens Institute of Technology
* *SUNY at Binghamton
* *SUNY at Buffalo
* *SUNY at Stony Brook
* *Texas A&M University
* *Texas Tech University
* *U.S. Geological Survey
* *University of Arizona
* *University of California, Berkeley
* *University of California, Irvine
* *University of California, Los Angeles
* *University of California, Merced
* *University of California, Riverside
* *University of California, San Diego
* *University of California, Santa Barbara
* *University of California, Santa Cruz
* *University of Central Florida
* *University of Colorado, Colorado Springs
* *University of Delaware
* *University of Florida
* *University of Georgia
* *University of Hawaii at Manoa
* *University of Houston
* *University of Illinois
* *University of Kentucky
* *University of Louisville
* *University of Maryland
* *University of Massachusetts
* *University of Miami
* *University of Michigan
* *University of Minnesota
* *University of Nevada, Las Vegas
* *University of Nevada, Reno
* *University of North Carolina at Charlotte
* *University of North Carolina
* *University of Notre Dame
* *University of Pacific
* *University of Pennsylvania
* *University of Rochester
* *University of South Florida
* *University of Southern California, Institute for Robotics and Intelligent Systems
* *University of Southern California, Signal and Image Processing
* *University of Southern California, Visual Processing Laboratory
* *University of Tennessee, Knoxville
* *University of Texas, Dallas
* *University of Texas
* *University of Utah
* *University of Virginia
* *University of Washington
* *University of West Florida
* *University of Wisconsin, Eau Claire
* *University of Wisconsin
* *Vanderbilt University
* *Vicarious Systems University
* *Virginia Tech
* *Washington University in St. Louis
* *Worchester Polytechnic Institute
* *Wright State University
* *Yale
109 for Research Group, US

Resizing Section: Image Manipulation -- Sampling, Reduction, Decimation, General Size Changes, Resizing (H3)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)

Restoration Section: Block Coding -- Reduce Block Artifacts, Effects, Deblocking (H3)
Section: Boundary Effects in Restoration (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: DCT Block Coding -- Block Artifacts in DCT (H4)
Section: Deblurring, Gaussian Blur (H3)
Section: Enhancement, Restoration of Document Images, Curls (H3)
Section: Fourier Analysis, Frequency Spectrum Restoration (H2)
Section: Historical Document Analysis (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Image Reconstruction (H2)
Section: Image Restoration -- General, Survey, Evaluations (H2)
Section: Image Restoration, Image Denoising (H1)
Section: Image Restoration: Filter Approaches (H2)
Section: Iterative, Recursive, Restoration Techniques (H3)
Section: Maximum Entropy in Restoration (H2)
Section: Minimum Entropy in Restoration (H3)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Multiresolution, Hierarchical Restoration Techniques (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Patch-Based Restoration, Denoising (H3)
Section: Space Varying Restoration, Adaptive Restoration (H2)
Section: Super Resolution and Restoration from Blurred Images, Motion Blur (H3)
Section: Super Resolution for Remote Sensing Applications (H3)
Section: Super Resolution, Restoration, for Atmosphere Effects, Turbulence (H3)
Section: Transmission Issues, Reduce Errors from Coding or Transmission (H3)
* On Some Bayesian/Regularization Methods for Image Restoration
* Restoring with Maximum Likelihood and Maximum Entropy
27 for Restoration

Retail Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Surveillance Systems, Applied to Retail Business, Shoppers, Shopping (H3)

Retargeting Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Image Based Rendering for Retargeting (H4)

Retina Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Retinal Identification Systems and Tecniques (H3)

Retinal Images Section: Diabetic Retinopathy, Retinal Analysis Application (H2)
Section: Glaucoma Retinopathy, Retinal Analysis Application (H2)
Section: Macular Degeneration Detection, Retinal Analysis Application (H2)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Optic Disc Location, Optic Disc Detection (H2)
Section: Retinal Images, Analysis of Eye, etc. (H1)
Section: Retinal Images, Angiography, Blood Vessels in the Eye (H2)
Section: Retinal Images, Optical Coherence Tomography, OCT (H2)
Section: Retinal Mosaic Generation (H3)
10 for Retinal Images

Retinal Mosaics Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Retinal Mosaic Generation (H3)

Retinal Vessels Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Retinal Images, Angiography, Blood Vessels in the Eye (H2)

Retinex Section: Color Constancy, Retinex (H2)
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Lightness and Retinex Theory

Retrieval Mechanism Section: Image Databases, Large Scale Systems, Web-Scale System (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: System Issues, Data Structures (H3)

Retrieval Section: Document Retrieval Systems, Databases and Issues, Libraries (H2)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Performance Evaluation of the Nearest Feature Line Method in Image Classification and Retrieval
* Texture Image Retrieval Using New Rotated Complex Wavelet Filters

Reverse Engineering Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Interactive Feature-Based Reverse Engineering of Mechanical Parts

Reversible Data Hiding Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Reversible Data Hiding, Steganography (H3)

Reversible Watermark Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Reversible Watermarking (H3)

RFM Definition:* Radon-Fourier-Mellin.
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Rational Function Models, Rational Polynomial Coefficients, Camera Specification (H3)

RGB-D Segmentation Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Range and Color, RGB-D Segmentation and Analysis (H3)

RGB-D Tracking Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Multi-Target Tracking with Multiple Sensors, Stereo, Depth, Range (H3)

RGB-D Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Gesture Systems, Using Depth Images, Range Data, Stereo Analysis for Gestures (H4)
Section: Human Action Recognition and Detection Using Depth, RGB-D, Kinect (H4)
Section: Human Pose from Depth, 3-D Data, Stereo, Multi-View Data (H3)
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, Shape from Motion for RGB-D Sensors, Kinect Motion (H2)
Section: Optical Flow Field Computations and Use (H)
Section: Scene Flow, Depth Image Flow, RGB-D (H2)
9 for RGB-D

Ribbons 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: Ribbon Descriptions (H2)
* Linear Feature Extraction

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

Rice Classification Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: Rice Crop Analysis, Production, Detection, Health, Change (H3)

Rice Yield Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: Rice Crop Analysis, Production, Detection, Health, Change (H3)

Ridge Detection Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Fingerprint Features, Minutiae, Ridges (H2)

Ridge Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: DEM, Surface Analysis for Ridges and Streams, Rivers, Drainage, Depressions (H2)
Section: Features of Surfaces and Range Data, Ridges, Edges (H3)

Rigid Motion Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Randomized Polygon Search for Planar Motion Detection

Road Detection Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Road Extraction in Radar, SAR, Lidar, Laser, Depth (H2)
Section: Road Following, Road Tracking Systems, Connecting Fragments, Extracting Fragments (H2)
Section: Road Network Detection, Road Extraction Systems (H1)
Section: Road Network Model Integration, Updating, and Change Detection (H2)
* Building and Road Extraction from Aerial Photographs
* Unbiased Detector of Curvilinear Structures, An
* Using Generic Geometric Models for Intelligent Shape Extraction
10 for Road Detection

Road Following Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Autonomous Vehicles, Low Level Image Processing (H2)
Section: Carnegie Mellon NAVLAB, AMBLER, etc. (H3)
Section: CMU Road Followers, ALVINN YARF MANIAC (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Road Following, Depth, Stereo Based, Off-Road, Safe Path (H3)
Section: Road, Path Following Operators (H2)
Section: Vehicle Control, Dickmanns (H3)
* Fundamental Limits of Bayesian Inference: Order Parameters and Phase Transitions for Road Tracking
9 for Road Following

Road Network Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: Road Network Detection, Road Extraction Systems (H1)

Road Signs Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: Road Signs, Traffic Signs, Traffic Lights, Objects along the Road, Inspections (H3)
* Detection of Vertical Pole-Like Objects in a Road Environment Using Vehicle-Based Laser Scanning Data

Robot Vision, Survey Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Model-Based Recognition in Robot Vision

Robust Line Fitting Section: Optical Flow Field Computations and Use (H)
* Detection of Independent Motion Using Directional Motion Estimation
* Direction-Selective Filters for Egomotion Estimation

Robust Technique 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: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Hough Transform -- Use and Theory (H1)
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: Robust Techniques, Robust Classification (H1)
* MINPRAN: A New Robust Estimator for Computer Vision
* Person Identification Using Multiple Cues
* Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography
* Robust Clustering with Applications in Computer Vision
* Robust Method for Surface Reconstruction, A
* Robust Sequential Estimator: A General-Approach and Its Application to Surface Organization in Range Data, The
14 for Robust Technique

ROC Analysis Section: Error Estimation, Classification Accuracy (H3)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

Rocks Section: Geological Analysis, Rocks (H3)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)

ROI Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Region of Interest Detection, ROI (H2)

Rolling Shutter Camera Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Rolling Shutter and Shape from Motion (H2)

Rolling Shutter Section: Motion Analysis -- Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Rolling Shutter Rectification, Alignment, Stabilization (H2)

Rooftop Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: Roof Structure, 3-D (H2)

Rotation Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Rotation Only (H2)

Rotational Symmetric Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Rotational Symmetry (H3)

Rotational Symmetry Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Rotational Symmetry (H3)

Roughness Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Surface Roughness, Rough Surfaces (H3)

Route Planning Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Planning Vehicle Position, Path Planning or Route Planning (H3)

Routing Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Traffic, Routing, Travel Time, Evaluation (H4)

RPC Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Rational Function Models, Rational Polynomial Coefficients, Camera Specification (H3)

RST Definition:* Rotation, Scale and Translation.

Rubber Sheet Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Surfaces, Rubber Sheets, Plates (H2)

Rule Based Analysis Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Natural Object Recognition

Rule Based Systems Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Expert Systems for Image Processing: Knowledge-Based Composition of Image Analysis Processes

Run Length Code Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Run-Length Coding Representations and Operations (H2)
* Representation of Contours and Regions for Efficient Computer Search
* Sequential Approach to the Extraction of Shape Features, A
* Statistical-Methods to Compare the Texture Features of Machined Surfaces
* Two-Dimensional Run-Encoding for Quadtree Representation

Index for "s"


Last update:15-Jul-17 21:08:59
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