Keith Price Bibliography keyword Listing for r

Keywords r

Radar * ATR -- Model, Object Based Radar and SAR Recognition (H3)
* ATR -- Radar, SAR Applications (H2)
* Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Fusion, Radar Data (H3)
* Ground Penetrating Radar, Buried Objects, UXO, Landmines (H3)
* Radar, Extraction of Features, Segmentation (H2)
* Radar, SAR Analysis (H1)
* Radar, Speckle Analysis and Removal, Speckle Reduction, Despeckle (H2)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Road Extraction in Radar and SAR (H2)
11 for Radar

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

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

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

Range Data, Registration * Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* 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 * Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* 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 Segmentation * 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Region Techniques for Range and Surfaces (H2)

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

Range * Fusion, Range and Intensity Data (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)

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

RANSAC * Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* 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
* Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography

Rate-Distortion * General Rate-Distortion Tradeoff Issues, Single Images (H3)
* General Rate-Quality, Rate Distortion, Rate Control, Error Tradeoffs for Video (H3)
* Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* MPEG Rate-Distortion Trade-Offs, Transmissions Issues (H3)
* Rate-Quality, Rate Distortion for DCT Coded Images, Wavelet Coding (H4)
* Rate-Quality, Rate Distortion, Rate Control, Error Tradeoffs for AVC/H.264 (H4)

Rate Control * General Rate-Quality, Rate Distortion, Rate Control, Error Tradeoffs for Video (H3)
* Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Rate-Quality, Rate Distortion for DCT Coded Images, Wavelet Coding (H4)
* Rate-Quality, Rate Distortion, Rate Control, Error Tradeoffs for AVC/H.264 (H4)

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

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

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

Real Time, Stereo * Stereo: Real Time Systems (H1)
* Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)

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

Recognition by Parts * 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 * 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Target Recognition with Tracking, Recognition in Sequences (H2)
* 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
7 for Recognition

Recognition, ATR * ATR Applications (H1)
* Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)

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

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

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

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

Recognize Aerial Images * Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* 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
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* 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 * Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* USC Airport Analysis Systems (H1)

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

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

Recognize Buildings * Building Analysis and Detection Systems (H1)
* Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* CMU Building Systems (H2)
* UMass Building Extraction Systems (H2)
* USC Building Systems (H2)

Recognize Characters * 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* 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 * 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 * Cursive Script Recognition Systems (H3)
* 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 * 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Structured Description of Complex Objects

Recognize Drainage Networks * 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 * 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* 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 * Books, Collections, Overviews, General, and Surveys (H)
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* 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 * Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Inference of Structure: Hands

Recognize Handwriting * Cursive Script Recognition Systems (H3)
* OCR, Document Analysis and Character Recognition Systems (H)
* 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 * 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* 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 * Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Hierarchical Object Recognition Using Libraries of Parameterized Model Sub-Parts

Recognize Range Data * 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* 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 * Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* Road Following, Road Tracking Systems, Connecting Fragments, Extracting Fragments (H2)
* 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 * OCR, Document Analysis and Character Recognition Systems (H)
* DRACAP: Drawing Capture for Electronic Schematics

Recognize Structures * 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 * 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-POLY: A Robot Vision System for Recognizing Objects in Occluded Environments
* 3D-Profile Method for Object Recognition, The
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* 3-D Object Recognition from Pose Estimation or Alignment (H2)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* 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
* Optimal Recognition of 3-D Objects By Search: Generic Models
* 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 * 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
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* 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

Reconfigurable Mesh * 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Reconfigurable Mesh Architectures and Algorithms (H3)
* Building a Quadtree and Its Applications on a Reconfigurable Mesh

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

Reconstruction * 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Electrical Impedance Tomography (H2)
* Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Image Reconstruction (H2)
* Lossless, Reconstructions from Wavelet Coded Images (H4)
* Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Reconstruction from Coded Images, Error Recovery (H3)
* Surveys, Overviews, Evaluations and Analysis of 3-D Reconstructions (H2)
* Tomographic Image Generation, Reconstruction (H2)
* Robust and Efficient Fourier-Mellin Transform Approximations for Gray-Level Image Reconstruction and Complete Invariant Description
12 for Reconstruction

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

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

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

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

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

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

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

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

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

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

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

Registration * Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* Change Detection, Damage Assessment (H3)
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Image Registration Techniques (H2)
* Register 3-D Surfaces, Range Registration (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Site Model Registration, Georeference, and Change Detection, Map Update (H2)
* 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
12 for Registration

Registration, 3-D * Register 3-D Surfaces, Range Registration (H3)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Surface Matching, Deformable Surface Matching (H2)

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

Regularization * 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Optical Flow Field Computations and Use (H)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* 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

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

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

Relaxation * 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Improving Edges by Neighborhood Processing, Relaxation (H2)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Optical Flow Field Computations and Use (H)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Segmentation by Thresholding, Quantization, or Relaxation (H2)
* Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* 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
52 for Relaxation

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

Relaxation, Discrete * Discrete Relaxation Methods (H2)
* Discrete Relaxation Theoretical Issues (H3)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)

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

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

Relaxation, Evaluation * 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
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Relaxation Based Techniques (H3)

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

Remote Sensing * *Earth Observation and Remote Sensing
* *Earth Observation Magazine
* *Image and Signal Processing for Remote Sensing III
* *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
* Analysis of Maps (H3)
* Books, Collections, Overviews, General, and Surveys (H)
* Building Analysis and Detection Systems (H1)
* Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* Change Detection, Damage Assessment (H3)
* Classification for Crops, Ground Cover, Land Use, Land Cover, Remote Sensing (H3)
* CMU Building Systems (H2)
* CMU MAPS Image Database System (H1)
* General Cartography Issues (H1)
* General Site Model Use, Program Surveys (H1)
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Map Analysis, Analysis of Map data, Map Processing (H2)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* OCR, Document Analysis and Character Recognition Systems (H)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* Recognition Systems Applied to Specific Applications (H1)
* Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
* Remote Sensing Issues (H2)
* Road Following, Road Tracking Systems, Connecting Fragments, Extracting Fragments (H2)
* Road Network Detection, Road Extraction Systems (H1)
* Road Network Model Integration, Updating, and Change Detection (H2)
* Site Model Construction and Evaluation (H2)
* Site Model Registration, Georeference, and Change Detection, Map Update (H2)
* SRI General Cartography Systems (H1)
* UMass Building Extraction Systems (H2)
* 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
41 for Remote Sensing

Rendering * Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
* Disparity field and depth map coding for multiview 3D image generation

Representation * Books, Collections, Overviews, General, and Surveys (H)
* Geometry of Visual Space (H3)
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Role of Representation in Vision (H3)
* System Issues, Data Structures (H3)

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

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

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

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

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

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

Representation, Log Mapping * 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Complex Log Mapping, Algorithms and Sensors (H2)
* 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 * 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Representation of Parts, Part-Based Models (H1)

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

Representation, Pyramid * 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* 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 * 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Quadtree Representations (H2)

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

Representation, Scale-Space * 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 * 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* SuperQuadric Representations (H1)

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

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

Research Group, Australia * *Australian National University, The
* *Cooperative Research Center for Sensor Signal and Image Processing
* *Curtin University
* *Monash University
* *National ICT Australia
* *University of Adelaide, The
* *University of New South Wales
* *University of Technology, Sydney
* *University of Western Australia
9 for Research Group, Australia

Research Group, Austria * *Graz University of Technology
* *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 Li�ge

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

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

Research Group, Company * *AccuSoft
* *ActivEye
* *Adept
* *Avaya Labs
* *Charles River Analytics, Inc.
* *Delphi Electronics and Safety
* *Digital Equipment Corp.
* *Epson Research and Development
* *GE Research
* *Gentec
* *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
* *Imagineer Systems
* *Intel Corp.
* *MERL: Mitsubishi Electric Research Laboratories
* *Microsoft Research
* *Palo Alto Research Center
* *Pattern Recogniton Company
* *Robot Vision 2 Inc.
* *Samsung Digital Media Solutions Lab
* *Sarnoff Research
* *Siemens VDO Automotive
* *Smith-Kettlewell Eye Research Institute
* *SRI AI Center
* *Videre Design
* *Virage
* *Willow Garage
33 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 * *Pascal: Pattern Analysis, Statistical Modelling and Computational Learning

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

Research Group, France * *Ecole Centrale Paris
* *Eurecom
* *INRIA Lorraine
* *INRIA Rh�ne-Alpes IMAG
* *INRIA Rh�ne-Alpes
* *INRIA Sophia Antipolis
* *INRIA
* *INSA Lyon
* *IRISA/INRIA Rennes
* *RealViz
* *Telecom Paris
* *Universite Paris IX Dauphine
* *Universit� de Bourgogne
* *Universit� Louis Pasteur, Strasbourg
14 for Research Group, France

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

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

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

Research Group, Israel * *Hebrew University
* *Technion Israel Institute of Technology
* *Tel Aviv University
* *Weizmann Institute of Science

Research Group, Italy * *Fondazione Bruno Kessler
* *Istituto Elettrotechnico Nazionale, IEN
* *Politecnico di Milano
* *University of Bologna
* *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
13 for Research Group, Italy

Research Group, Japan * *Gunma University
* *Japan Advanced Institute of Science and Technology, JAIST
* *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
14 for Research Group, Japan

Research Group, Korea * *KAIST: Korean Advanced Institute of Science and Technology
* *Korea University
* *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 * *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, Spain * *Institute for Industrial Automation
* *Pompeu Fabra University
* *Rovira i Virgili University
* *Universidad de Las Palmas de Gran Canaria
* *Universidad Politechnica de Valencia
* *Universidad Rey Juan Carlos
* *Universitat de Girona
* *University Jaume I
* *University of Autononoma de Barcelona
* *University of Granada
* *University of Politecnica Madrid
* *University of the Balearic Islands
12 for Research Group, Spain

Research Group, Sweden * *Computational Vision and Active Perception Laboratory
* *Halmstad University
* *Linkoping University
* *Lund University
* *Uppsala University

Research Group, Switzerland * *Ecole Polytechnique F�d�rale de Lausanne
* *IDIAP
* *Swiss Federal Institute of Technology in Zurich
* *Swiss Federal Institute of Technology
* *University of Basel
* *University of Bern
* *University of Geneva
7 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
* *University of Amsterdam
* *University of Groninen
* *University of Twente
* *Utrecht University

Research Group, Turkey * *Bilkent University
* *Bogazi�i University
* *Cankaya University
* *Sabanci University

Research Group, United Kingdom * *Cranfield University

Research Group, US Government * *Electro Technical Laboratory
* *Jet Proplusion Laboratory
* *Journal of Research National Bureau of Standards

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

Retinal Images * Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
* Retinal Images, Analysis of Eye, etc. (H1)

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

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

Retrieval Mechanism * Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* System Issues, Data Structures (H3)

Retrieval * Document Retrieval Systems, Databases and Issues, Libraries (H2)
* Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* OCR, Document Analysis and Character Recognition Systems (H)
* 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 * 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Interactive Feature-Based Reverse Engineering of Mechanical Parts

Ribbons * 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Ribbon Descriptions (H2)
* Linear Feature Extraction

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

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

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

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

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

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

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

Robust Technique * 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
* Hough Transform -- Use and Theory (H1)
* Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
* 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 * Error Estimation, Classification Accuracy (H3)
* Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)

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

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

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

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

Run Length Code * 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* 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: 1-Oct-08 09:45:31
Use price@usc.edu for comments.