Computer Vision - Eccv 2008 - Forsyth David (Curatore); Torr Philip (Curatore); Zisserman Andrew (Curatore) | Libro Springer Berlin Heidelberg 10/2008 -

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forsyth david (curatore); torr philip (curatore); zisserman andrew (curatore) - computer vision - eccv 2008

Computer Vision - ECCV 2008 10th European Conference on Computer Vision, Marseille, France, October 12-18, 2008, Proceedings, Part III

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Lingua: Inglese
Pubblicazione: 10/2008
Edizione: 2008


Welcome to the 2008EuropeanConference onComputer Vision. These proce- ings are the result of a great deal of hard work by many people. To produce them, a total of 871 papers were reviewed. Forty were selected for oral pres- tation and 203 were selected for poster presentation, yielding acceptance rates of 4.6% for oral, 23.3% for poster, and 27.9% in total. Weappliedthreeprinciples.First,sincewehadastronggroupofAreaChairs, the ?nal decisions to accept or reject a paper rested with the Area Chair, who wouldbeinformedbyreviewsandcouldactonlyinconsensuswithanotherArea Chair. Second, we felt that authors were entitled to a summary that explained how the Area Chair reached a decision for a paper. Third, we were very careful to avoid con?icts of interest. Each paper was assigned to an Area Chair by the Program Chairs, and each Area Chair received a pool of about 25 papers. The Area Chairs then identi?ed and rankedappropriatereviewersfor eachpaper in their pool, and a constrained optimization allocated three reviewers to each paper. We are very proud that every paper received at least three reviews. At this point, authors were able to respond to reviews. The Area Chairs then needed to reach a decision. We used a series of procedures to ensure careful review and to avoid con?icts of interest. ProgramChairs did not submit papers. The Area Chairs were divided into three groups so that no Area Chair in the group was in con?ict with any paper assigned to any Area Chair in the group.


Matching.- 3D Non-rigid Surface Matching and Registration Based on Holomorphic Differentials.- Learning Two-View Stereo Matching.- SIFT Flow: Dense Correspondence across Different Scenes.- Learning+Features.- Discriminative Sparse Image Models for Class-Specific Edge Detection and Image Interpretation.- Non-local Regularization of Inverse Problems.- Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks.- Learning Optical Flow.- Poster Session III.- Optimizing Binary MRFs with Higher Order Cliques.- Multi-camera Tracking and Atypical Motion Detection with Behavioral Maps.- Automatic Image Colorization Via Multimodal Predictions.- CSDD Features: Center-Surround Distribution Distance for Feature Extraction and Matching.- Detecting Carried Objects in Short Video Sequences.- Constrained Maximum Likelihood Learning of Bayesian Networks for Facial Action Recognition.- Robust Scale Estimation from Ensemble Inlier Sets for Random Sample Consensus Methods.- Efficient Camera Smoothing in Sequential Structure-from-Motion Using Approximate Cross-Validation.- Semi-automatic Motion Segmentation with Motion Layer Mosaics.- Unified Frequency Domain Analysis of Lightfield Cameras.- Segmenting Fiber Bundles in Diffusion Tensor Images.- View Point Tracking of Rigid Objects Based on Shape Sub-manifolds.- Generative Image Segmentation Using Random Walks with Restart.- Background Subtraction on Distributions.- A Statistical Confidence Measure for Optical Flows.- Automatic Generator of Minimal Problem Solvers.- A New Baseline for Image Annotation.- Behind the Depth Uncertainty: Resolving Ordinal Depth in SFM.- Sparse Long-Range Random Field and Its Application to Image Denoising.- Output Regularized Metric Learning with Side Information.- Student-t Mixture Filter for Robust, Real-Time Visual Tracking.- Photo and Video Quality Evaluation: Focusing on the Subject.- The Bi-directional Framework for Unifying Parametric Image Alignment Approaches.- Direct Bundle Estimation for Recovery of Shape, Reflectance Property and Light Position.- A Probabilistic Cascade of Detectors for Individual Object Recognition.- Scale-Dependent/Invariant Local 3D Shape Descriptors for Fully Automatic Registration of Multiple Sets of Range Images.- Star Shape Prior for Graph-Cut Image Segmentation.- Efficient NCC-Based Image Matching in Walsh-Hadamard Domain.- Object Recognition by Integrating Multiple Image Segmentations.- A Linear Time Histogram Metric for Improved SIFT Matching.- An Extended Phase Field Higher-Order Active Contour Model for Networks and Its Application to Road Network Extraction from VHR Satellite Images.- A Generic Neighbourhood Filtering Framework for Matrix Fields.- Multi-scale Improves Boundary Detection in Natural Images.- Estimating 3D Trajectories of Periodic Motions from Stationary Monocular Views.- Unsupervised Learning of Skeletons from Motion.- Multi-layered Decomposition of Recurrent Scenes.- SERBoost: Semi-supervised Boosting with Expectation Regularization.- View Synthesis for Recognizing Unseen Poses of Object Classes.- Projected Texture for Object Classification.- Prior-Based Piecewise-Smooth Segmentation by Template Competitive Deformation Using Partitions of Unity.- Vision-Based Multiple Interacting Targets Tracking via On-Line Supervised Learning.- An Incremental Learning Method for Unconstrained Gaze Estimation.- Partial Difference Equations over Graphs: Morphological Processing of Arbitrary Discrete Data.- Real-Time Shape Analysis of a Human Body in Clothing Using Time-Series Part-Labeled Volumes.- Kernel Codebooks for Scene Categorization.- Multiple Tree Models for Occlusion and Spatial Constraints in Human Pose Estimation.- Structuring Visual Words in 3D for Arbitrary-View Object Localization.- Multi-thread Parsing for Recognizing Complex Events in Videos.- Signature-Based Document Image Retrieval.- An Effective Approach to 3D Deformable Surface Tracking.- MRFs.- Belief Propagation with Directional Statistics for Solving the Shape-from-Shading Problem.- A Convex Formulation of Continuous Multi-label Problems.- Beyond Loose LP-Relaxations: Optimizing MRFs by Repairing Cycles.

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Condizione: Nuovo
Collana: Lecture Notes in Computer Science
Dimensioni: 235 x 155 mm Ø 1276 gr
Formato: Brossura
Pagine Arabe: 826
Pagine Romane: xix

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