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Statistical Methods in Video Processing: ECCV 2004 Workshop SMVP 2004, Prague, Czech Republic, May 16, 2004, Revised Selected Papers

✍ Scribed by H. Cornelius, R. à Ñra, D. Martinec, T. Pajdla, O. Chum, J. Matas (auth.), Dorin Comaniciu, Rudolf Mester, Kenichi Kanatani, David Suter (eds.)


Publisher
Springer-Verlag Berlin Heidelberg
Year
2004
Tongue
English
Leaves
207
Series
Lecture Notes in Computer Science 3247
Edition
1
Category
Library

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✦ Synopsis


The 2nd International Workshop on Statistical Methods in Video Processing, SMVP 2004, was held in Prague, Czech Republic, as an associated workshop of ECCV 2004, the 8th European Conference on Computer Vision. A total of 30 papers were submitted to the workshop. Of these, 17 papers were accepted for presentation and included in these proceedings, following a double-blind review process. The workshop had 42 registered participants. The focus of the meeting was on recent progress in the application of - vanced statistical methods to solve computer vision tasks. The one-day scienti?c program covered areas of high interest in vision research, such as dense rec- struction of 3D scenes, multibody motion segmentation, 3D shape inference, errors-in-variables estimation, probabilistic tracking, information fusion, optical ?owcomputation,learningfornonstationaryvideodata,noveltydetectionin- namic backgrounds, background modeling, grouping using feature uncertainty, and crowd segmentation from video. We wish to thank the authors of all submitted papers for their interest in the workshop.Wealsowishtothankthemembersofourprogramcommitteeandthe external reviewers for their commitment of time and e?ort in providing valuable recommendations for each submission. We are thankful to Vaclav Hlavac, the General Chair of ECCV 2004, and to Radim Sara, for the local organization of the workshop and registration management. We hope you will ?nd these proceedings both inspiring and of high scienti?c quality.

✦ Table of Contents


Front Matter....Pages -
Towards Complete Free-Form Reconstruction of Complex 3D Scenes from an Unordered Set of Uncalibrated Images....Pages 1-12
Geometric Structure of Degeneracy for Multi-body Motion Segmentation....Pages 13-25
Virtual Visual Hulls: Example-Based 3D Shape Inference from Silhouettes....Pages 26-37
Unbiased Errors-In-Variables Estimation Using Generalized Eigensystem Analysis....Pages 38-49
Probabilistic Tracking of the Soccer Ball....Pages 50-60
Multi-Model Component-Based Tracking Using Robust Information Fusion....Pages 61-70
A Probabilistic Approach to Large Displacement Optical Flow and Occlusion Detection....Pages 71-82
Mean-Shift Blob Tracking with Kernel-Color Distribution Estimate and Adaptive Model Update Criterion....Pages 83-93
Combining Simple Models to Approximate Complex Dynamics....Pages 94-104
Online Adaptive Gaussian Mixture Learning for Video Applications....Pages 105-116
Novelty Detection in Image Sequences with Dynamic Background....Pages 117-128
A Framework for Foreground Detection in Complex Environments....Pages 129-140
A Background Maintenance Model in the Spatial-Range Domain....Pages 141-152
A New Robust Technique for Stabilizing Brightness Fluctuations in Image Sequences....Pages 153-164
Factorization of Natural 4 Γ— 4 Patch Distributions....Pages 165-174
Parametric and Non-parametric Methods for Linear Extraction....Pages 175-186
Crowd Segmentation Through Emergent Labeling....Pages 187-198
Back Matter....Pages -

✦ Subjects


Image Processing and Computer Vision; Computer Graphics; Pattern Recognition; Probability and Statistics in Computer Science; Artificial Intelligence (incl. Robotics); Algorithm Analysis and Problem Complexity


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