Index for tu,

Tu, C. * 3-D robust range feature extraction tool for industrial automation applications, A
* Error Resilient Pre/Post-Filtering for DCT-Based Block Coding Systems
* Time-varying Surface Appearance: Acquisition, Modeling, and Rendering
* Undersampled Boundary Pre-/Postfilters for Low Bit-Rate DCT-Based Block Coders
* Wiener Filter-Based Error Resilient Time-Domain Lapped Transform

Tu, C.H.[Chang He] * Continuous Collision Detection between Two 2 D Curved-Edge Polygons under Rational Motions
* GPU-Based Algorithm for Building Stochastic Clustered-Dot Screens, A
Includes: Tu, C.H.[Chang He] Tu, C.H.[Chang-He]

Tu, C.J.[Cheng Jie] * Adaptive runlength coding
* Context-based entropy coding of block transform coefficients for image compression
* Multiple Description Image Coding with Prediction Compensation
* On context-based entropy coding of block transform coefficients
* Optimal Block Boundary Pre/Postfiltering for Wavelet-Based Image and Video Compression
* Over-sampled and under-sampled Pre/post-filters for block DCT coders
Includes: Tu, C.J.[Cheng Jie] Tu, C.J.[Cheng-Jie]

Tu, C.T.[Ching Ting] * Facial Occlusion Reconstruction: Recovering Both the Global Structure and the Local Detailed Texture Components
Includes: Tu, C.T.[Ching Ting] Tu, C.T.[Ching-Ting]

Tu, G.F.[Guo Fang] * Robust H.263+ video transmission using partial backward decodable bit stream (PBDBS)
Includes: Tu, G.F.[Guo Fang] Tu, G.F.[Guo-Fang]

Tu, J.L.[Ji Lin] * Accurate Head Pose Tracking in Low Resolution Video
* Audio-Visual Affect Recognition through Multi-Stream Fused HMM for HCI
* Calibrating Head Pose Estimation in Videos for Meeting Room Event Analysis
* EAVA: A 3D Emotive Audio-Visual Avatar
* Face as Mouse Through Visual Face Tracking
* Face localization via hierarchical Condensation with Fisher boosting feature selection
* Learning a Person-Independent Representation for Precise 3D Pose Estimation
* Locating Nosetips and Estimating Head Pose in Images by Tensorposes
* Online Updating Appearance Generative Mixture Model for Meanshift Tracking
* Variational Shift Invariant Probabilistic PCA for Face Recognition
* Variational Transform Invariant Mixture of Probabilistic PCA
Includes: Tu, J.L.[Ji Lin] Tu, J.L.[Ji-Lin]
11 for Tu, J.L.

Tu, L.T. * Design Methodology for Highly Reliable Character Recognition Systems, A
* Offline Recognition of Chinese Handwriting by Multifeature and Multilevel Classification

Tu, L.V.[Le Van] * Robust and Highly Customizable Recognition of On-Line Handwritten Japanese Characters

Tu, P.[Peter] * email: Tu, P.[Peter]: Tu AT Balltown.cma.com
* Automatic Face Recognition from Skeletal Remains
* Boosted deformable model for human body alignment
* Computer-aided facial reconstruction using skulls
* Extraction of events from 3D volumes of seismic data
* Identification of events from 3D volumes of seismic data
* Recognizing Objects in Cluttered Images Using Subgraph Isomorphism
* Seismic Time Section Analysis Using Machine Vision
* Shape and Appearance Context Modeling
* Site calibration for large indoor scenes
* Statistical Significance as an Aid to System Performance Evaluation
* Surface reconstruction via Helmholtz reciprocity with a single image pair
* What are customers looking at?
Includes: Tu, P.[Peter] Tu, P.
13 for Tu, P.

Tu, P.H. * Activity Recognition using Visual Tracking and RFID
* Collaborative Real-Time Control of Active Cameras in Large-Scale Surveillance Systems.
* Crowd Segmentation Through Emergent Labeling
* Detecting and counting people in surveillance applications
* Distributed data association and filtering for multiple target tracking
* Face Model Fitting on Low Resolution Images
* Improved Face Model Fitting on Video Sequences
* Multi-Frame Super-Resolution for Face Recognition
* Simultaneous Estimation of Segmentation and Shape
* Unified Crowd Segmentation
* View adaptive detection and distributed site wide tracking
Includes: Tu, P.H. Tu, P.H.[Peter H.]
11 for Tu, P.H.

Tu, S.F.[Shu Fen] * Statistical Approach for Ownership Identification of Digital Images, A
Includes: Tu, S.F.[Shu Fen] Tu, S.F.[Shu-Fen]

Tu, S.K.[Shu Kang] * Video object tracking using adaptive Kalman filter
Includes: Tu, S.K.[Shu Kang] Tu, S.K.[Shu-Kang]

Tu, T.M. * Computation Reduction of the Maximum-Likelihood Classifier Using the Winograd Identity
* Empirical Mode Decomposition Approach for Iris Recognition, An
* Novel Approach for Iris Recognition Using Local Edge Patterns, A
* oblique subspace projection approach for mixed pixel classification in hyperspectral images, An
* Recognizing Human Iris by Modified Empirical Mode Decomposition
* Robust spatial watermarking technique for colour images via direct saturation adjustment
* Target-cluster fusion approach for classifying high resolution IKONOS imagery
Includes: Tu, T.M. Tu, T.M.[Te-Ming]
7 for Tu, T.M.

Tu, T.Y.[Tsing Yee] * Character recognition by stochastic sectionalgram approach
Includes: Tu, T.Y.[Tsing Yee] Tu, T.Y.[Tsing-Yee]

Tu, X. * Robust 3D Clue-Based Video Segmentation for Video Indexing

Tu, X.W. * 3-D Information Derivation from a Pair of Binocular Images
* Trinocular Vision System For A Mobile Robot, A

Tu, Y.K. * Efficient Rate-Distortion Estimation for H.264/AVC Coders
* Fast variable-size block motion estimation for efficient H.264/AVC encoding
* Rate-Distortion Modeling for Efficient H.264/AVC Encoding
Includes: Tu, Y.K. Tu, Y.K.[Yu-Kuang]

Tu, Y.S. * Storage-Constrained and Entropy-Constrained Classified Vector Quantization

Tu, Y.T. * Classification of Machine Printed and Handwritten Texts Using Character Block Layout Variance

Tu, Z.[Zhuown] * Integrating Bottom-Up/Top-Down for Object Recognition by Data Driven Markov Chain Monte Carlo

Tu, Z.W.[Zhuo Wen] * Auto-context and its application to high-level vision tasks
* Automated Extraction of the Cortical Sulci Based on a Supervised Learning Approach
* Brain Anatomical Structure Segmentation by Hybrid Discriminative/Generative Models
* Detecting Object Boundaries Using Low-, Mid-, and High-level Information
* Feature Mining for Image Classification
* Framework for Automatic Recognition of Spatial Features from Mobile Mapping Imagery, A
* Graph-shifts: Natural image labeling by dynamic hierarchical computing
* Image Parsing: Unifying Segmentation, Detection, and Recognition
* Image Segmentation by Data-Driven Markov Chain Monte Carlo
* Improving Shape Retrieval by Learning Graph Transduction
* Integrated Framework for Image Segmentation and Perceptual Grouping, An
* Learning Based Approach for 3D Segmentation and Colon Detagging, A
* Learning based coarse-to-fine image registration
* Learning Generative Models via Discriminative Approaches
* MRF Labeling with a Graph-Shifts Algorithm
* Multiple Component Learning for Object Detection
* Parsing Images into Region and Curve Processes
* Parsing Images into Regions, Curves, and Curve Groups
* Probabilistic 3D Polyp Detection in CT Images: The Role of Sample Alignment
* Probabilistic Boosting-Tree: Learning Discriminative Models for Classification, Recognition, and Clustering
* Range Image Segmentation by an Effective Jump-Diffusion Method
* Shape Matching and Recognition: Using Generative Models and Informative Features
* Shape matching and registration by data-driven EM
* Simultaneous Learning and Alignmennt: Multi-Instance and Multi-Pose Learning
* Stochastic Algorithm for 3D Scene Segmentation and Reconstruction, A
* Supervised Learning of Edges and Object Boundaries
Includes: Tu, Z.W.[Zhuo Wen] Tu, Z.W.[Zhuo-Wen]
26 for Tu, Z.W.

Index for "t"


Last update:24-Nov-08 09:52:31
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