Spatial Coherence for Visual Motion Analysis

First International Workshop, SCVMA 2004, Prague, Czech Republic, May 15, 2004. Revised Papers

  • W. James MacLean
Conference proceedings

DOI: 10.1007/11676959

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3667)

Table of contents (11 papers)

  1. Front Matter
  2. Structure from Periodic Motion
    Serge Belongie, Josh Wills
    Pages 16-24
  3. 3D SSD Tracking from Uncalibrated Video
    Dana Cobzas, Martin Jagersand
    Pages 25-37
  4. Comparison of Edge-Driven Algorithms for Model-Based Motion Estimation
    Hendrik Dahlkamp, Artur Ottlik, Hans-Hellmut Nagel
    Pages 38-50
  5. On the Relationship Between Image and Motion Segmentation
    Adrian Barbu, Song Chun Zhu
    Pages 51-63
  6. Motion Detection Using Wavelet Analysis and Hierarchical Markov Models
    Cédric Demonceaux, Djemâa Kachi-Akkouche
    Pages 64-75
  7. Segregation of Moving Objects Using Elastic Matching
    Vishal Jain, Benjamin B. Kimia, Joseph L. Mundy
    Pages 76-90
  8. Local Descriptors for Spatio-temporal Recognition
    Ivan Laptev, Tony Lindeberg
    Pages 91-103
  9. A Generative Model of Dense Optical Flow in Layers
    Anitha Kannan, Brendan Frey, Nebojsa Jojic
    Pages 104-114
  10. Analysis and Interpretation of Multiple Motions Through Surface Saliency
    Mircea Nicolescu, Changki Min, Gérard Medioni
    Pages 115-126
  11. Dense Optic Flow with a Bayesian Occlusion Model
    Kevin Koeser, Christian Perwass, Gerald Sommer
    Pages 127-139
  12. Back Matter

About these proceedings


Motionanalysisisacentralproblemincomputervision,andthepasttwodecades have seen important advances in this ?eld. However, visual motion is still often considered on a pixel-by-pixel basis, even though this ignores the fact that image regions corresponding to a single object usually undergo motion that is highly correlated. Further, it is often of interest to accurately measure the boundaries of moving regions. In the case of articulated motion, especially human motion, discovering motion boundaries is non-trivial but an important task nonetheless. Another related problem is identifying and grouping multiple disconnected - gions moving with similar motions, such as a ?ock of geese. Early approaches focused on measuring motion of either the boundaries or the interior, but s- dom both in unison. For several years now, attempts have been made to include spatial coherence terms into algorithms for 2- and 3-D motion recovery, as well as motion boundary estimation. This volume is a record of papers presented at the First International Wo- shop on Spatial Coherence for Visual Motion Analysis, held May 15th, 2004 in Prague, in conjunction with the European Conference on Computer Vision (LNCS 3021–4). The workshop examined techniques for integrating spatial - herence constraints during motion analysis of image sequences. The papers were revised after the workshop to allow for incorporation of feedback from the workshop.


3D 3D imaging algorithm algorithms classification cognition computer vision image analysis image sequence motion detection motion estimation multiple motion detection neural networks segmentation spatio-temporal recognition

Editors and affiliations

  • W. James MacLean
    • 1
  1. 1.University of TorontoTorontoCanada

Bibliographic information

  • Copyright Information Springer-Verlag Berlin Heidelberg 2006
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Computer Science
  • Print ISBN 978-3-540-32533-8
  • Online ISBN 978-3-540-32534-5
  • Series Print ISSN 0302-9743
  • Series Online ISSN 1611-3349