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    A study on smoothing for particle-filtered 3D human body tracking

    133818_133818.pdf (723.6Kb)
    Access Status
    Open access
    Authors
    Peursum, Patrick
    Venkatesh, Svetha
    West, Geoffrey
    Date
    2009
    Type
    Journal Article
    
    Metadata
    Show full item record
    Citation
    Peursum, Patrick and Venkatesh, Svetha and West, Geoffrey. 2009. A study on smoothing for particle-filtered 3D human body tracking. International Journal of Computer Vision. 87 (1-2): pp. 53-74.
    Source Title
    International Journal of Computer Vision
    DOI
    10.1007/s11263-009-0205-5
    ISSN
    09205691
    Faculty
    School of Science and Computing
    Department of Computing
    Faculty of Science and Engineering
    Remarks

    The original publication is available at : www.springerlink.com

    URI
    http://hdl.handle.net/20.500.11937/48073
    Collection
    • Curtin Research Publications
    Abstract

    Stochastic models have become the dominant means of approaching the problem of articulated 3D human body tracking, where approximate inference is employed to tractably estimate the high-dimensional (~30D) posture space. Of these approximate inference techniques, particle filtering is the most commonly used approach. However filtering only takes into account past observations - almost no body tracking research employs smoothing to improve the filtered inference estimate, despite the fact that smoothing considers both past and future evidence and so should be more accurate. In an effort to objectively determine the worth of existing smoothing algorithms when applied to human body tracking, this paper investigates three approximate smoothed-inference techniques: particle-filtered backwards smoothing, variational approximation and Gibbs sampling. Results are quantitatively evaluated on both the HUMANEVA dataset as well as a scene containing occluding clutter. Surprisingly, it is found that existing smoothing techniques are unable to provide much improvement on the filtered estimate, and possible reasons as to why are explored and discussed.

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