Articulated Body Motion Capture by Stochastic Search

Authors: Deutscher, Jonathan¹; Reid, Ian²

Source: International Journal of Computer Vision, Volume 61, Number 2, February 2005 , pp. 185-205(21)

Publisher: Springer

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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.

Keywords: human motion capture; visual tracking; particle filtering; genetic algorithms

Document Type: Research article

DOI: http://dx.doi.org/10.1023/B:VISI.0000043757.18370.9c

Affiliations: 1: Department of Engineering Science, University of Oxford, Oxford, OX13PJ, United Kingdom, Email: jdeutsch@robots.ox.ac.uk 2: Department of Engineering Science, University of Oxford, Oxford, OX13PJ, United Kingdom, Email: ian.reid@eng.ox.ac.uk

Publication date: 2005-02-01