TABU Search
[Provide a short definition]
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Tabu Search (H3)
* Future paths for Integer Programming and Links to Artificial Intelligence
Tactile Sensing
[Provide a short definition]
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (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)
* Computational Approaches for Processing and Analysis of Tactile Information
* Feature-Based Tactile Object Recognition
* Integrated System for Active Exploration Using Contact and Non-Contact Sensors, An
* Model-Based Recognition and Localization from Sparse Range or Tactile Data
7 for Tactile Sensing
Tamper Detection
[Provide a short definition]
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Tamper Detection (H3)
Section: Video Data Hiding, Data Hiding in Video, Video Steganography (H3)
Target Pose Estimation
[Provide a short definition]
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Registration and Exploitation of Multi-pass Airborne Synthetic Aperture Radar Images
Target Recognition
[Provide a short definition]
* *Automatic ObjectTarget Recognition VIII
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: ATR Applications, Automatic Target Recognition (H1)
Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
* Image Clutter Characterization for Object Detection in High Clutter Images
Target Tracking
[Provide a short definition]
Section: Mean-Shift Tracking Techniques (H3)
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)
Section: Region and Object Tracking, Templates, Template Update, Template Drift (H3)
Section: Region, Object, Target Tracking (H2)
Section: Target and Feature Tracking, Multi-Object, Multiple Objects, Multiple Target (H3)
Section: Target Tracking Systems, Real-Time Issues (H3)
Section: Target Tracking Techniques, Evaluation, Comparison, Survey (H3)
Section: Target Tracking Techniques, Motion Model, Prediction, Control (H3)
Section: Target Tracking Techniques, Multiple Trackers, Multiple Models, Fusion (H4)
Section: Target Tracking Techniques, Occlusions, Clutter (H4)
Section: Target Tracking Techniques, Particle Filter Techniques (H4)
Section: Target Tracking Techniques, Tests (H4)
Section: Target Tracking, Active, Camera Following, Real Time Issues, Hardware (H3)
Section: Target Tracking, Collision Detection (H3)
Section: Target Tracking, Multiple Sensors, Multiple Cameras, Multi-Camera Tracking (H3)
Section: Tracking for Weather, Clouds (H3)
Section: Tracking Known Objects, Models, Points, Robot Hand-Eye Tracking (H3)
18 for Target Tracking
Task Planning
[Provide a short definition]
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Task Planning and Action Coordination in Integrated Sensor-Based Robots
Telepresence
[Provide a short definition]
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Telepresence, Immersion, for Instruction, Training (H4)
Section: Telepresence, Teleoperation, Immersion (H3)
Television
[Provide a short definition]
Section: Distributed Video Coding (H2)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: HDTV Issues, Coding, Transmission (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Transmission Issues, Special Issues, Surveys (H3)
Section: Transmission, Television, and Television Coding (H2)
* Method of Coding TV Signals Based on Edge Detection, A
7 for Television
Template Decomposition
[Provide a short definition]
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
* Simplified Algorithm for Approximate Separable Decomposition of Morphological Templates, A
Template Matching
[Provide a short definition]
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Optical Flow Field Computations and Use (H)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Template Matching Techniques (H2)
* Correlation-Relaxation-Labeling Framework for Computing Optical Flow: Template Matching from a New Perspective, A
* Object Detection Using Focused Color DCT Matching
* Online Recognition of Handwritten Symbols
* Person Identification Using Multiple Cues
* Representation and Recognition of Handwritten Digits Using Deformable Templates
* Vision-Based Road Detection in Automotive Systems: A Real-Time Expectation-Driven Approach
13 for Template Matching
Template Update
[Provide a short definition]
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Region and Object Tracking, Templates, Template Update, Template Drift (H3)
Terrain
[Provide a short definition]
Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: DEM, DSM, DTM, Evaluations, Valdiation, Surveys, Overviews (H2)
Section: Terrain Extraction, DEM, DTM, DSM (H1)
Tetrahedral Representation
[Provide a short definition]
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Local Topological Parameters in a Tetrahedral Representation
Text Analysis
[Provide a short definition]
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Reading Chess
Text Detection
[Provide a short definition]
Section: OCR, Document Analysis and Character Recognition Systems (H)
Section: Text Detection, Find Text in General Scenes, Scene Text, Color Documents (H4)
Text Line Extraction
[Provide a short definition]
Section: Cursive Script, Text Line Segmentation, Script Line, Segmentation, Text Line Extraction (H4)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Text Recognition
[Provide a short definition]
Section: Cursive Script, Text Line Segmentation, Script Line, Segmentation, Text Line Extraction (H4)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Texture Analysis
[Provide a short definition]
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: Texture Discrimination and Classification (H2)
Section: Texture for Defect Detection (H2)
* Is There Any Texture in the Image?
Texture Boundary
[Provide a short definition]
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Texture Boundaries and Edges (H2)
Texture Edges
[Provide a short definition]
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Texture Edge Operators (H3)
Texture Mapping
[Provide a short definition]
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Texture Mapping, Terrain Visualization, Terrain Rendering, DEM Rendering (H4)
Texture Models
[Provide a short definition]
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Texture Models, Analysis Techniques (H2)
Texture Recognition
[Provide a short definition]
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* Real-Time Recognition with the Entire Brodatz Texture Database
Texture Segmentation
[Provide a short definition]
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Multi-Scale, Pyramid Texture Segmentation Approaches (H2)
Section: Noise Models in Segmentation (H2)
Section: Textures and Color for Segmentation (H2)
Texture Synthesis
[Provide a short definition]
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: Texture Synthesis (H2)
* Image repairing: robust image synthesis by adaptive ND tensor voting
* Multispectral Texture Synthesis Using Fractal Concepts
Texture
[Provide a short definition]
* *Visual Information Processing V
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Mammography, Texture Based Techniques, Wavelets (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Review, Comparison, Evaluation of Texture Analysis Techniques (H1)
Section: Texture Edge Operators (H3)
* Automatic Watershed Segmentation of Randomly Textured Color Images
* Comparative Study of Textural Analysis Techniques to Characterise Tissue from Intravascular Ultrasound
* Personal identification based on iris texture analysis
12 for Texture
Texture, Co-occurrence
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Co-occurrence Matrix Description Methods (H1)
Texture, Color
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Modeling and Identifying 3-D Color Textures
Texture, Evaluation
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Filtering for Texture Classification: A Comparative Study
* Optical Texture Analysis for Automatic Cytology and Histology: A Markovian Approach
* Theoretical Comparison of Texture Algorithms, A
Texture, Orientation
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Texture for Surface Orientation (H2)
Texture, Recognition
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Classification of Textures by Structural Analysis
Texture, Segmentation
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Texture Based Segmentation Techniques (H1)
Texture, Shape
Section: 3-D Shape from X -- Shading, Textures, Lasers, Structured Light, Focus, Line Drawings (H)
Section: Shape from Texture (H1)
Texture, Statistical
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Statistical Methods for Texture Description and Analysis (H1)
Section: Statistical Texture Classification (H2)
Texture, Structural
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Structural Methods for Texture Description (H1)
Texture, Survey
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Statistical and Structural Approaches to Texture
* Texture Analysis Anno 1983
Texture, Transforms
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Transforms for Texture -- Fourier (H1)
Textures, Filters
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Filter Approaches to Texture (H2)
Section: Wavelets, Gabor Filters for Texture (H3)
Textures, Fractals
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Fractals for Texture Analysis and Description, Fractal Dimension (H2)
Textures, Oriented
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Oriented Texture, Directional Texture Patterns (H2)
Textures, Structural
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Multi-scale Region Detector, A
Textures, Synthesis
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Models for Texture Synthesis (H3)
Section: Texture Synthesis (H2)
Thai Characters
[Provide a short definition]
Section: OCR, Document Analysis and Character Recognition Systems (H)
* Recognition of Handprinted Thai Characters Using Loop Structures
Theil-Sen Estimator
[Provide a short definition]
Section: Edge Detection and Analysis, Lines, Segments, Curves, Corners, Hough Transform (H)
* Efficient Randomized Algorithms for Robust Estimation of Circular Arcs and Aligned Ellipses
Thinning Techniques
[Provide a short definition]
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Distance Transforms, Distance Functions, Distance Measures (H2)
Section: Skeletons and Axial Descriptions - Medial Axis Transform (MAT) etc. (H
* Thinning Methodologies: A Comprehensive Survey
Thinning
[Provide a short definition]
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: Thinning Algorithms in Three Dimensions (H3)
Section: Thinning Algorithms (H2)
* Specialized Edge-Trackers for Contour Extraction and Line-Thinning
Three-Dimensional Data
[Provide a short definition]
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Morphology for Range and 3-D data (H3)
Three-Dimensional Models
[Provide a short definition]
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: MRI, Enhancement, Noise and Artifact Reduction (H2)
Section: MRI, Surveys, Overviews, Evaluations (H2)
Section: Segmentation, Features, Models from Magnetic Resonance Data, MRI (H2)
Three-Dimensional Skeleton
[Provide a short definition]
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
Section: Medial Axis Transform, MAT, Skeletons in Three Dimensions (H2)
Three Dimensional Computations
[Provide a short definition]
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Basic Algorithms for Three-Dimensional Computations (H1)
Three Dimensional Points
[Provide a short definition]
Section: 2-D Points with 3-D Structures (H2)
Section: 3-D Points with 3-D Structures (H2)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Three Views, Stereo
Section: Stereo Using Three Views, Trinocular Stereo (H1)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Threshold Selection
[Provide a short definition]
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Histogram Analysis for Threshold Selection and Segmentation (H2)
Threshold Selection, Survey
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Survey of Threshold Selection Techniques, A
* Survey of Thresholding Techniques, A
Thresholding
[Provide a short definition]
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Comment on Using the Uniformity Measure for Performance-Measure in Image Segmentation
Thresholds, Evaluation
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
* Comparative Performance Study of Several Global Thresholding Techniques for Segmentation, A
* Threshold Evaluation Techniques
Tiled Images
[Provide a short definition]
Section: 2-D Feature Analysis, Extraction and Representations, Shape, Skeletons, Texture (H)
* Fast Linear Transformation For Tiled Images
Time Series
[Provide a short definition]
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Section: Time Series Analysis, One-D Waveform Analysis, One-D Signals (H2)
Time to Collision
[Provide a short definition]
Section: Focus of Expansion and Other Features (H2)
Section: Obstacle Detection, Time to Collision Techniques (H2)
Section: Optical Flow Field Computations and Use (H)
* Analyzing Looming Motion Components from Their Spatiotemporal Spectral Signature
Time to Impact
[Provide a short definition]
Section: Focus of Expansion and Other Features (H2)
Section: Optical Flow Field Computations and Use (H)
TIN
[Provide a short definition]
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: Triangulated Surface Models, Mesh Models, Mesh Descriptions, 3-D Meshes (H3)
* Iterative TIN Generation from Digital Elevation Models
* Radial Sweep Algorithm for Constructing Triangulated Irregular Networks, The
Tomography
[Provide a short definition]
Section: Diffraction Tomography (H2)
Section: Electrical Impedance Tomography (H2)
Section: Iterative Reconstruction Techniques (H2)
Section: Liver Disease, Tomography, CAT Analysis (H3)
Section: Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models (H)
Section: Optical Tomography, Infrared Tomography (H2)
Section: Statistical, Bayesian Tomographic Image Reconstruction (H3)
Section: Tomographic Image Generation, CAT, CT, Reconstruction (H2)
Section: Tomographic Image Generation, Cone-Beam, Fan-Beam, Helical, Spiral Reconstruction (H2)
Section: Tomographic Images, Artifact Removal, Enhancement (H2)
Section: Tomographic Images, CAT Scans (Computed Axial Tomography) (H
Section: Tomographic Images, CAT, CT, Overviews, Surveys (H2)
Section: Tomographic Object Construction, Object Extraction, Analysis, Organs (H2)
13 for Tomography
Topological Structure
[Provide a short definition]
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
* Resolving View Sensitivity With Surface Locality
Topology
[Provide a short definition]
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: Digital Topology (H2)
Section: Three Dimensional Geometry and Topology, Computational Geometry (H2)
Total Variation
[Provide a short definition]
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Total Variation Restoration (H3)
Tracking Objects
[Provide a short definition]
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
* Visual Servoing using Correlation Filters
Tracking
[Provide a short definition]
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Active Contours, Snakes or Deformable Curves (H2)
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (H)
Section: Active Vision: Foveal Sensing (H2)
Section: Active Vision: Gaze Control (H2)
Section: Arm Tracking, Arm Pose for Gestures (H4)
Section: Contours Through a Sequence (H3)
Section: Crowds, Tracking Multiple People, Multiple Pedestrian Tracking (H4)
Section: Face Recognition, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics (H)
Section: Hand Tracking for Gestures (H3)
Section: Hand-Eye Coordination (H2)
Section: Head Motion, Head Tracking, Tracking Faces in Video (H1)
Section: Human Activities, Sports, Player Tracking (H4)
Section: Long Sequence Matching and Motion (H2)
Section: Long Sequences, Motion Matching (H3)
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Motion Estimates Using 5 or More Frames (H2)
Section: Obstacle Dectection, Other Vehicles, Objects on the Road (H3)
Section: Region, Object, Target Tracking (H2)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)
Section: Snakes, Applications (H3)
Section: Snakes, Contours, Motion Tracking (H2)
Section: Snakes, General Techniques and Descriptions (H3)
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
Section: Target Recognition with Tracking, Recognition in Sequences (H2)
Section: Tracking Animals, Animal Gait (H4)
Section: Tracking Faces, Heads Using Color Models (H3)
Section: Tracking of Moving Objects and Matching in Sequences (H1)
Section: Tracking People with 3D Models, Articulation Models (H4)
Section: Tracking People with Multiple Cameras, Stereo, or Depth (H4)
Section: Tracking People, Human Tracking, Pedestrian Tracking (H3)
Section: Tracking People, Re-Identification Issues, Occlusions (H4)
* Analysis of Two-Dimensional Movement Using Fourier Descriptors
* Error Propagation in two-sensor 3D position estimation
* Incremental Focus of Attention for Robust Visual Tracking
* Recognition via Consensus of Local Moments of Brightness and Orientation
* Toward a System for the Interpretation of Moving Light Display
* Vehicle Segmentation and Classification Using Deformable Templates
38 for Tracking
Tracking, Clouds
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Tracking for Weather, Clouds (H3)
Tracking, Nonrigid
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Nonrigid, Deformable Motion Tracking (H3)
Tracking, People
Section: Implementations and Applications, Databases, QBIC, Video Analysis, Hardware and Software, Inspection (H)
* GPU-Accelerated Tracking of the Motion of 3D Articulated Figure
Trademarks
[Provide a short definition]
Section: Analysis of Graphics, Symbols, Trademarks, Logos, Icons (H3)
Section: OCR, Document Analysis and Character Recognition Systems (H)
Traffic Analysis
[Provide a short definition]
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Traffic Signal Control, Traffic Analysis, Not Image Analysis (H4)
Section: Traffic Surveillance, Analysis of Traffic (H3)
* Analogical Representation of Space and Time
Traffic Signs
[Provide a short definition]
Section: Active Vision, Camera Calibration, Mobile Robots, Navigation, Road Following (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 Signs, Traffic Signs, Objects along the Road, Inspections (H3)
* Detection of Vertical Pole-Like Objects in a Road Environment Using Vehicle-Based Laser Scanning Data
* regular polygon detector, The
Traffic Surveillance
[Provide a short definition]
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
Section: Traffic Surveillance, Analysis of Traffic (H3)
Training Set
[Provide a short definition]
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Training Set Size, Analysis, Selection (H2)
Transcoding
[Provide a short definition]
Section: Hardware and Systems for Transcoding, Conversions (H3)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Transfer Learning
[Provide a short definition]
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Section: Transfer Learning from Other Classes (H3)
Transform Coding
[Provide a short definition]
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Transform Coding -- General (H2)
Transform
[Provide a short definition]
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
* Multiplierless PR Quadrature Mirror Filters for Subband Image-coding
Transforms
[Provide a short definition]
Section: Computational Vision, Regularization, Connectionist, Morphology, Scale-Space, Perceptual Grouping, Wavelets, Color, Sensors, Optical, Laser, Radar (H)
Section: Filters and Transforms for Recognition or Detection (H1)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Lifting Operator, Transform (H4)
Section: Transforms, Radon, Haar, Hadamard, etc. (H2)
Translation Estimation
[Provide a short definition]
Section: Optical Flow Field Computations and Use (H)
* Performance of Camera Translation Direction Estimators from Optical-flow: Analysis, Comparison, and Theoretical Limits, The
Transmission
[Provide a short definition]
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
Section: Image Processing, Restoration, Enhancement, Filters, Image and Video Coding (H)
Section: Image Transmission Issues, Progressive Transmission -- Still Images (H3)
Section: Lossless Coding, Lossless Compression, Transmission (H2)
Section: New Unsorted Entries, and Other Miscellaneous Papers (H)
Section: Transmission Issues, ATM Networks (H3)
Section: Transmission Issues, Coding (H3)
Section: Transmission Issues, Internet, Packet Video (H3)
Section: Transmission Issues, Modulation, Multiplexing, Radio, Cell Phone (H2)
Section: Transmission Issues, Reduce Errors from Coding or Transmission (H3)
Section: Transmission Issues, Special Issues, Surveys (H3)
Section: Transmission Issues, Wireless Systems, Wireless Networks, Mobile Systems (H3)
Section: Video Phone Issues, Coding (H3)
13 for Transmission
Tree Classifiers
[Provide a short definition]
Section: Decision Trees (H2)
Section: Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms (H)
Tree Searching
[Provide a short definition]
Section: Matching and Recognition Using Volumes, High Level Vision Techniques, Invariants (H)
Section: Matching Using Tree Searching Techniques (H2)
Trees
[Provide a short definition]
Section: Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR (H)
Section: Trees, Individual Trees, Tree Crowns (H2)
Trees, Sigma
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Sigma-Tree Q A Symbolic Spatial Data Model, The
Triangulated Models
[Provide a short definition]
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: General Triangulation Models, Delaunay (H4)
Section: Triangulated Surface Models, Mesh Models, Mesh Descriptions, 3-D Meshes (H3)
Triangulation
[Provide a short definition]
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Surface Griding with Intrinsic Parameters
Trifocal Tensor
[Provide a short definition]
Section: Motion -- Feature-Based, Long Range, Motion and Structure Estimates, Tracking, Surveillance, Activities (H)
* Threading Fundamental Matrices
Trilinear Tensor
[Provide a short definition]
Section: Stereo: Three Dimensional Descriptions from Two or More Views, Binocular, Trinocular (H)
* On Degeneracy of Linear Reconstruction From Three Views: Linear Line Complex and Applications
Trinocular Stereo
[Provide a short definition]
Section: 3-D Object Description and Computation Techniques, Surfaces, Deformable, View Generation, Video Conferencing (H)
* Segmented Shape Description from 3-View Stereo
Turbulence
[Provide a short definition]
Section: Motion Analysis --Low-Level, Image Level Analysis, Mosaic Generation, Super Resolution, Shape from Motion (H)
Section: Super Resolution, Restoration, for Atmosphere Effects, Turbulence (H3)
Two Dimensional Histograms
[Provide a short definition]
Section: 2-D Region Segmentation Techniques, Snakes, Active Contours (H)
Section: Two-Dimensional Histogram Analysis for Segmentation (H2)
Two Dimensional Points
[Provide a short definition]
Section: 2-D Points with 2-D Structures, Point Matching, Features (H2)
Section: Registration, Matching and Recognition Using Points, Lines, Regions, Areas, Surfaces (H)