Computer Vision -- Eccv 2006: 9th European Conference on Computer Vision, Graz, Austria, May 7-13, 2006, Proceedings, Part III

ISBN-13: 9783540338369 / Angielski / Miękka / 2006 / 654 str.

Ale Leonardis

Opis

Constitutes the refereed proceedings of the 9th European Conference on Computer Vision, 2006. This book covers a range of issues in computer vision, on recognition, statistical models and visual learning, 3D reconstruction and multi-view geometry, energy minimization, tracking and motion, segmentation, shape from X, visual tracking, and more.

Spis treści

Recognition II.- Blind Vision.- Object Detection by Contour Segment Networks.- Sparse Flexible Models of Local Features.- Shape from X.- Differential Geometric Consistency Extends Stereo to Curved Surfaces.- Resolution-Enhanced Photometric Stereo.- The 4-Source Photometric Stereo Under General Unknown Lighting.- Poster Session III.- Incorporating Non-motion Cues into 3D Motion Segmentation.- Multi-camera Tracking and Segmentation of Occluded People on Ground Plane Using Search-Guided Particle Filtering.- Learning Semantic Scene Models by Trajectory Analysis.- Multivariate Relevance Vector Machines for Tracking.- Real-Time Upper Body Detection and 3D Pose Estimation in Monoscopic Images.- Gait Recognition Using a View Transformation Model in the Frequency Domain.- Multiview Geometry and 3D Methods.- Video Mensuration Using a Stationary Camera.- Revisiting the Brightness Constraint: Probabilistic Formulation and Algorithms.- Triangulation for Points on Lines.- A Fast Line Segment Based Dense Stereo Algorithm Using Tree Dynamic Programming.- Describing and Matching 2D Shapes by Their Points of Mutual Symmetry.- Oriented Visibility for Multiview Reconstruction.- Integrating Surface Normal Vectors Using Fast Marching Method.- Statistical Models and Visual Learning.- Learning Discriminative Canonical Correlations for Object Recognition with Image Sets.- Statistical Priors for Efficient Combinatorial Optimization Via Graph Cuts.- Sampling Representative Examples for Dimensionality Reduction and Recognition – Bootstrap Bumping LDA.- Studying Aesthetics in Photographic Images Using a Computational Approach.- Located Hidden Random Fields: Learning Discriminative Parts for Object Detection.- Learning Compositional Categorization Models.- EMD-L 1: An Efficient and Robust Algorithm for Comparing Histogram-Based Descriptors.- Face/Gesture/Action Detection and Recognition.- 2D and 3D Multimodal Hybrid Face Recognition.- Robust Attentive Behavior Detection by Non-linear Head Pose Embedding and Estimation.- Human Pose Tracking Using Multi-level Structured Models.- Context-Aided Human Recognition – Clustering.- Robust Expression-Invariant Face Recognition from Partially Missing Data.- Segmentation and Grouping.- An Integral Solution to Surface Evolution PDEs Via Geo-cuts.- Detecting Doctored JPEG Images Via DCT Coefficient Analysis.- A Learning Based Approach for 3D Segmentation and Colon Detagging.- Fast, Quality, Segmentation of Large Volumes – Isoperimetric Distance Trees.- Segmentation of High Angular Resolution Diffusion MRI Modeled as a Field of von Mises-Fisher Mixtures.- Globally Optimal Active Contours, Sequential Monte Carlo and On-Line Learning for Vessel Segmentation.- Matching.- Optimal Multi-frame Correspondence with Assignment Tensors.- Kernel-Predictability: A New Information Measure and Its Application to Image Registration.- Algebraic Methods for Direct and Feature Based Registration of Diffusion Tensor Images.- Rethinking the Prior Model for Stereo.- Aligning Sequences and Actions by Maximizing Space-Time Correlations.- Simultaneous Nonrigid Registration of Multiple Point Sets and Atlas Construction.- Enforcing Temporal Consistency in Real-Time Stereo Estimation.- The Alignment Between 3-D Data and Articulated Shapes with Bending Surfaces.- Visual Tracking.- Feature Harvesting for Tracking-by-Detection.- Effective Appearance Model and Similarity Measure for Particle Filtering and Visual Tracking.- Tracking and Labelling of Interacting Multiple Targets.- Level-Set Curve Particles.