Articulated Body Motion Capture by Stochastic Search

  • Authors:
  • Jonathan Deutscher;Ian Reid

  • Affiliations:
  • Department of Engineering Science, University of Oxford, Oxford, United Kingdom OX13PJ;Department of Engineering Science, University of Oxford, Oxford, United Kingdom OX13PJ

  • Venue:
  • International Journal of Computer Vision
  • Year:
  • 2005

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Abstract

We develop a modified particle filter which is shown to be effective at searching the high-dimensional configuration spaces (c. 30 + dimensions) encountered in visual tracking of articulated body motion. The algorithm uses a continuation principle, based on annealing, to introduce the influence of narrow peaks in the fitness function, gradually. The new algorithm, termed annealed particle filtering, is shown to be capable of recovering full articulated body motion efficiently. A mechanism for achieving a soft partitioning of the search space is described and implemented, and shown to improve the algorithm's performance. Likewise, the introduction of a crossover operator is shown to improve the effectiveness of the search for kinematic trees (such as a human body). Results are given for a variety of agile motions such as walking, running and jumping.