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Statistical Methods in Video Processing : ECCV 2004 Workshop SMVP 2004, Prague, Czech Republic, May 16, 2004, Revised Selected Papers / edited by Dorin Comaniciu, Kenichi Kanatani, Rudolf Mester, David Suter.

LIBRA Q341 .P7 2004
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Format:
Book
Contributor:
Comaniciu, Dorin, editor.
Kanatani, Kenʼichi, 1947- editor.
Mester, Rudolf, editor.
Suter, David (Computer scientist), editor.
SpringerLink (Online service)
Series:
Computer Science (Springer-11645)
Lecture notes in computer science 0302-9743 ; 3247.
Lecture Notes in Computer Science, 0302-9743 ; 3247
Language:
English
Subjects (All):
Optical data processing.
Computer graphics.
Pattern perception.
Mathematical statistics.
Artificial intelligence.
Algorithms.
Image Processing and Computer Vision.
Computer Graphics.
Pattern Recognition.
Probability and Statistics in Computer Science.
Artificial Intelligence.
Algorithm Analysis and Problem Complexity.
Local Subjects:
Image Processing and Computer Vision.
Computer Graphics.
Pattern Recognition.
Probability and Statistics in Computer Science.
Artificial Intelligence.
Algorithm Analysis and Problem Complexity.
Physical Description:
1 online resource (VIII, 200 pages).
Edition:
First edition 2004.
Contained In:
Springer eBooks
Place of Publication:
Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2004.
System Details:
text file PDF
Summary:
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.
Contents:
3D Geometry
Towards Complete Free-Form Reconstruction of Complex 3D Scenes from an Unordered Set of Uncalibrated Images
Geometric Structure of Degeneracy for Multi-body Motion Segmentation
Virtual Visual Hulls: Example-Based 3D Shape Inference from Silhouettes
Unbiased Errors-In-Variables Estimation Using Generalized Eigensystem Analysis
Tracking
Probabilistic Tracking of the Soccer Ball
Multi-Model Component-Based Tracking Using Robust Information Fusion
A Probabilistic Approach to Large Displacement Optical Flow and Occlusion Detection
Mean-Shift Blob Tracking with Kernel-Color Distribution Estimate and Adaptive Model Update Criterion
Combining Simple Models to Approximate Complex Dynamics
Background Modeling
Online Adaptive Gaussian Mixture Learning for Video Applications
Novelty Detection in Image Sequences with Dynamic Background
A Framework for Foreground Detection in Complex Environments
A Background Maintenance Model in the Spatial-Range Domain
Image/Video Analysis
A New Robust Technique for Stabilizing Brightness Fluctuations in Image Sequences
Factorization of Natural 4 × 4 Patch Distributions
Parametric and Non-parametric Methods for Linear Extraction
Crowd Segmentation Through Emergent Labeling.
Other Format:
Printed edition:
ISBN:
978-3-540-30212-4
9783540302124
Access Restriction:
Restricted for use by site license.

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