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Full Body Motion Tracking in Monocular Images Using Particle Swarm Optimization

  • Bogusław Rymut
  • Tomasz Krzeszowski
  • Bogdan Kwolek
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7267)

Abstract

The estimation of full body pose in monocular images is a very difficult problem. In 3D-model based motion tracking the challenges arise as at least one-third of degrees of freedom of the human pose that needs to be recovered is nearly unobservable in any given monocular image. In this paper, we deal with high dimensionality of the search space through estimating the pose in a hierarchical manner using Particle Swarm Optimization. Our method fits the projected body parts of an articulated model to detected body parts at color images with support of edge distance transform. The algorithm was evaluated quantitatively through the use of the motion capture data as ground truth.

Keywords

Particle Swarm Optimization Motion Capture Data Human Body Model Monocular Image Human Motion Capture 
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 2012

Authors and Affiliations

  • Bogusław Rymut
    • 1
  • Tomasz Krzeszowski
    • 1
  • Bogdan Kwolek
    • 1
  1. 1.Polish-Japanese Institute of Information TechnologyWarszawaPoland

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