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Statistical Methods in Video Processing

ECCV 2004 Workshop SMVP 2004, Prague, Czech Republic, May 16, 2004, Revised Selected Papers

  • Dorin Comaniciu
  • Rudolf Mester
  • Kenichi Kanatani
  • David Suter
Conference proceedings SMVP 2004

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3247)

Table of contents

  1. Front Matter
  2. 3D Geometry

    1. H. Cornelius, R. Šára, D. Martinec, T. Pajdla, O. Chum, J. Matas
      Pages 1-12
    2. Yasuyuki Sugaya, Kenichi Kanatani
      Pages 13-25
    3. Kristen Grauman, Gregory Shakhnarovich, Trevor Darrell
      Pages 26-37
  3. Tracking

    1. Kyuhyoung Choi, Yongdeuk Seo
      Pages 50-60
    2. Bogdan Georgescu, Dorin Comaniciu, Tony X. Han, Xiang Sean Zhou
      Pages 61-70
    3. Christoph Strecha, Rik Fransens, Luc Van Gool
      Pages 71-82
    4. Leonid Taycher, John W. Fisher III, Trevor Darrell
      Pages 94-104
  4. Background Modeling

    1. Fredrik Kahl, Richard Hartley, Volker Hilsenstein
      Pages 117-128
    2. Junxian Wang, How-Lung Eng, Alvin H. Kam, Wei-Yun Yau
      Pages 129-140
    3. Daniel Kottow, Mario Köppen, Javier Ruiz-del-Solar
      Pages 141-152
  5. Image/Video Analysis

    1. François Pitié, Rozenn Dahyot, Francis Kelly, Anil Kokaram
      Pages 153-164
    2. Kostadin Koroutchev, José R. Dorronsoro
      Pages 165-174
    3. Benedicte Bascle, Xiang Gao, Visvanathan Ramesh
      Pages 175-186
    4. Peter H. Tu, Jens Rittscher
      Pages 187-198
  6. Back Matter

About these proceedings

Introduction

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.

Keywords

3D 3D shape inference Variable calculus computational geometry computer vision image processing image sequences learning modeling multi-body motion segmentation statistical methods statistical pattern recognition system analysis video processing

Editors and affiliations

  • Dorin Comaniciu
    • 1
  • Rudolf Mester
    • 2
  • Kenichi Kanatani
    • 3
  • David Suter
    • 4
  1. 1.Integrated Data Systems Dept.Siemens Corporate ResearchPrincetonUSA
  2. 2.Visual Sensorics and Information Processing LabJ.W. Goethe UniversityFrankfurtGermany
  3. 3.Department of Computer ScienceOkayama UniversityOkayamaJapan
  4. 4.Institute for Vision Systems Engineering, Department of Electrical and Computer Systems EngineeringMonash UniversityAustralia

Bibliographic information

  • DOI https://doi.org/10.1007/b104157
  • Copyright Information Springer-Verlag Berlin Heidelberg 2004
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Springer Book Archive
  • Print ISBN 978-3-540-23989-5
  • Online ISBN 978-3-540-30212-4
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site