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Computer Science - Image Processing | Computer Vision -- ECCV 2006 - 9th European Conference on Computer Vision, Graz, Austria, May

Computer Vision -- ECCV 2006

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

Leonardis, Aleš, Bischof, Horst, Pinz, Axel (Eds.)

2006, XVII, 649 p. Also available online.

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These are the proceedings of the 9th European Conference on Computer Vision (ECCV 2006), the premium European conference on computer vision, held in Graz, Austria, in May 2006. Inresponsetoourconferencecall,wereceived811papers,thelargestnumber of submissions so far. Finally, 41 papers were selected for podium presentation and 151 for presentation in poster sessions (a 23. 67% acceptance rate). The double-blind reviewing process started by assigning each paper to one of the 22 area chairs, who then selected 3 reviewers for each paper. After the reviewswerereceived,theauthorswereo?eredthepossibilitytoprovidefeedback on the reviews. On the basis of the reviews and the rebuttal of the authors, the area chairs wrote the initial consolidation report for each paper. Finally, all the area chairs attended a two-day meeting in Graz, where all decisions on acceptance/rejectionweremade. At that meeting,the areachairsresponsiblefor similar sub-?elds thoroughly evaluated the assigned papers and discussed them in great depth. Again, all decisions were reached without the knowledge of the authors’ identity. We are fully aware of the fact that reviewing is always also subjective, and that somegood papers might havebeen overlooked;however,we tried our best to apply a fair selection process. The conference preparation went smoothly thanks to several people. We ?rst wish to thank the ECCV Steering Committee for entrusting us with the orga- zationoftheconference. Wearegratefultotheareachairs,whodidatremendous job in selecting the papers, and to more than 340 ProgramCommittee members and 220 additional reviewers for all their professional e?orts.

Content Level » Research

Keywords » 3D - 3D reconstruction - Computer Vision - Stereo - Triangulation - camera calibration - cognition - computational geometry - face recognition - geometric computation - learning - modeling - object tracking - optimization - programming

Related subjects » Artificial Intelligence - Image Processing

Table of contents 

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.

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