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2001
IEEE

Automatic Partitioning of High Dimensional Search Spaces Associated with Articulated Body Motion Capture

11 years 4 months ago
Automatic Partitioning of High Dimensional Search Spaces Associated with Articulated Body Motion Capture
Particle filters have proven to be an effective tool for visual tracking in non-gaussian, cluttered environments. Conventional particle filters however do not scale to the problem of Human Motion Capture (HMC) because of the large number of degrees of freedom involved. Annealed Particle Filtering (APF), introduced by Deutscher et al [3], tackled this by layering the search space and was shown to be a very effective tool for HMC. In this paper we improve upon and extend the APF in two ways. First we develop a hierarchical search strategy which automatically partitions the search space without any explicit representation of the partitions. Then we introduce a crossover operator (similar to that found in Genetic Algorithms) which improves the ability of the tracker to search different partitions in parallel. We present results for a simple example to demonstrate the new algorithm's implementation and then apply it to the considerably more complex problem of Human Motion Capture with...
Jonathan Deutscher, Andrew J. Davison, Ian D. Reid
Added 12 Oct 2009
Updated 12 Oct 2009
Type Conference
Year 2001
Where CVPR
Authors Jonathan Deutscher, Andrew J. Davison, Ian D. Reid
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