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Dynamical Vision

ICCV 2005 and ECCV 2006 Workshops, WDV 2005 and WDV 2006, Beijing, China, October 21, 2005, Graz, Austria, May 13, 2006, Revised Papers

  • Conference proceedings
  • © 2007

Overview

Editors:
  1. René Vidal
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  2. Anders Heyden
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  3. Yi Ma
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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 4358)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

Included in the following conference series:

Conference proceedings info: WDV 2005. WDV 2006.

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Table of contents (24 papers)

  1. Front Matter

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  2. Motion Segmentation and Estimation

    1. The Space of Multibody Fundamental Matrices: Rank, Geometry and Projection

      • Xiaodong Fan, René Vidal
      Pages 1-17

    2. Direct Segmentation of Multiple 2-D Motion Models of Different Types

      • Dheeraj Singaraju, René Vidal
      Pages 18-33

    3. Motion Segmentation Using an Occlusion Detector

      • Doron Feldman, Daphna Weinshall
      Pages 34-47

    4. Robust 3D Segmentation of Multiple Moving Objects Under Weak Perspective

      • Levente Hajder, Dmitry Chetverikov
      Pages 48-59

    5. Nonparametric Estimation of Multiple Structures with Outliers

      • Wei Zhang, Jana Kǒsecká
      Pages 60-74

  3. Human Motion Analysis, Tracking and Recognition

    1. Articulated Motion Segmentation Using RANSAC with Priors

      • Jingyu Yan, Marc Pollefeys
      Pages 75-85

    2. Articulated-Body Tracking Through Anisotropic Edge Detection

      • David Knossow, Joost van de Weijer, Radu Horaud, Rémi Ronfard
      Pages 86-99

    3. Homeomorphic Manifold Analysis: Learning Decomposable Generative Models for Human Motion Analysis

      • Chan-Su Lee, Ahmed Elgammal
      Pages 100-114

    4. View-Invariant Modeling and Recognition of Human Actions Using Grammars

      • Abhijit S. Ogale, Alap Karapurkar, Yiannis Aloimonos
      Pages 115-126

  4. Dynamic Textures

    1. Segmenting Dynamic Textures with Ising Descriptors, ARX Models and Level Sets

      • Atiyeh Ghoreyshi, René Vidal
      Pages 127-141

    2. Spatial Segmentation of Temporal Texture Using Mixture Linear Models

      • Lee Cooper, Jun Liu, Kun Huang
      Pages 142-150

    3. Online Video Registration of Dynamic Scenes Using Frame Prediction

      • Alex Rav-Acha, Yael Pritch, Shmuel Peleg
      Pages 151-164

    4. Dynamic Texture Recognition Using Volume Local Binary Patterns

      • Guoying Zhao, Matti Pietikäinen
      Pages 165-177

  5. Motion Tracking

    1. A Rao-Blackwellized Parts-Constellation Tracker

      • Grant Schindler, Frank Dellaert
      Pages 178-189

    2. Bayesian Tracking with Auxiliary Discrete Processes. Application to Detection and Tracking of Objects with Occlusions

      • Patrick Pérez, Jaco Vermaak
      Pages 190-202

    3. Tracking of Multiple Objects Using Optical Flow Based Multiscale Elastic Matching

      • Xingzhi Luo, Suchendra M. Bhandarkar
      Pages 203-217

    4. Real-Time Tracking with Classifiers

      • Thierry Chateau, Vincent Gay-Belille, Frederic Chausse, Jean-Thierry Lapresté
      Pages 218-231

  6. Rigid and Non-rigid Motion Analysis

    1. A Probabilistic Framework for Correspondence and Egomotion

      • Justin Domke, Yiannis Aloimonos
      Pages 232-242

    2. Estimating the Pose of a 3D Sensor in a Non-rigid Environment

      • Adrien Bartoli
      Pages 243-256
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  1. Dynamical Vision

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About this book

Classical multiple-view geometry studies the reconstruction of a static scene - served by a rigidly moving camera. However, in many real-world applications the scene may undergo much more complex dynamical changes. For instance, the scene may consist of multiple moving objects (e.g., a tra?c scene) or arti- lated motions (e.g., a walking human) or even non-rigid dynamics (e.g., smoke, ?re, or a waterfall). In addition, some applications may require interaction with the scene through a dynamical system (e.g., vision-guided robot navigation and coordination). To study the problem of reconstructing dynamical scenes, many new al- braic, geometric, statistical, and computational tools have recently emerged in computer vision, computer graphics, image processing, and vision-based c- trol. The goal of the International Workshop on Dynamical Vision (WDV) is to converge di?erent aspects of the research on dynamical vision and to identify common mathematical problems, models, and methods for future research in this emerging and active area.

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