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‘Dynamism of a Dog on a Leash’ or Behavior Classification by Eigen-Decomposition of Periodic Motions

  • Roman Goldenberg
  • Ron Kimmel
  • Ehud Rivlin
  • Michael Rudzsky
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2350)

Abstract

Following Futurism, we show how periodic motions can be represented by a small number of eigen-shapes that capture the whole dynamic mechanism of periodic motions. Spectral decomposition of a silhouette of an object in motion serves as a basis for behavior classification by principle component analysis. The boundary contour of the walking dog, for example, is first computed efficiently and accurately. After normalization, the implicit representation of a sequence of silhouette contours given by their corresponding binary images, is used for generating eigen-shapes for the given motion. Singular value decomposition produces these eigen-shapes that are then used to analyze the sequence. We show examples of object as well as behavior classification based on the eigen-decomposition of the binary silhouette sequence.

Keywords

Feature Point Periodic Motion Parameterized Representation Implicit Representation Motion Period 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Roman Goldenberg
    • 1
  • Ron Kimmel
    • 1
  • Ehud Rivlin
    • 1
  • Michael Rudzsky
    • 1
  1. 1.Computer Science DepartmentTechnion—Israel Institute of TechnologyTechnion City, HaifaIsrael

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