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Complex Motion

First International Workshop, IWCM 2004, Günzburg, Germany, October 12-14, 2004. Revised Papers

  • Editors
  • Bernd Jähne
  • Rudolf Mester
  • Erhardt Barth
  • Hanno Scharr
Conference proceedings IWCM 2004

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3417)

Table of contents

  1. Front Matter
  2. Michael Felsberg
    Pages 1-13
  3. Per-Erik Forssén, Hagen Spies
    Pages 54-65
  4. Cicero Mota, Ingo Stuke, Til Aach, Erhardt Barth
    Pages 66-77
  5. Paul Ruhnau, Jing Yuan, Christoph Schnörr
    Pages 124-145
  6. Klas Nordberg, Fredrik Vikstén
    Pages 146-164
  7. Christoph Strecha, Rik Fransens, Luc Van Gool
    Pages 165-176
  8. Michael Sühling, Muthuvel Arigovindan, Christian Jansen, Patrick Hunziker, Michael Unser
    Pages 177-189
  9. Anton van den Hengel, Wojciech Chojnacki, Michael J. Brooks
    Pages 190-197
  10. Leonid Sigal, Ying Zhu, Dorin Comaniciu, Michael Black
    Pages 223-234
  11. Back Matter

About these proceedings

Introduction

The world we live in is a dynamic one: we explore it by moving through it, and many of the objects which we are interested in are also moving. Tra?c, for instance, is an example of a domain where detecting and processing visual motion is of vital interest, both in a metaphoric as well as in a purely literal sense. Visual communication is another important example of an area of science which is dominated by the need to measure, understand, and represent visual motion in an e?cient way. Visual motion is a subject of research which forces the investigator to deal withcomplexity;complexityinthesenseoffacinge?ectsofmotioninaverylarge diversity of forms, starting from analyzing simple motion in a changing envir- ment (illumination, shadows, . . . ), under adverse observation conditions, such as bad signal-to-noiseratio (low illumination, small-scaleprocesses, low-dosex-ray, etc. ), covering also multiple motions of independent objects, occlusions, and - ing as far as dealing with objects which are complex in themselves (articulated objects such as bodies of living beings). The spectrum of problems includes, but does not end at, objects which are not ‘bodies’ at all, e. g. , when anal- ing ?uid motion, cloud motion, and so on. Analyzing the motion of a crowd in a shopping mall or in an airport is a further example that implies the need to struggleagainsttheproblemsinducedbycomplexity.

Keywords

3D 3D motion Stereo camera grid classification computer vision feature extraction image analysis image reconstruction image segmentation image sequences motion estimation motion tracking object recognition pattern recogni

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-69866-1
  • Copyright Information Springer-Verlag Berlin Heidelberg 2007
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-69864-7
  • Online ISBN 978-3-540-69866-1
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349
  • Buy this book on publisher's site