Comparison of Silhouette Shape Descriptors for Example-based Human Pose Recovery

Ronald Walter Poppe, Mannes Poel

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    41 Citations (Scopus)
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    Automatically recovering human poses from visual input is useful but challenging due to variations in image space and the high dimensionality of the pose space. In this paper, we assume that a human silhouette can be extracted from monocular visual input. We compare three shape descriptors that are used in the encoding of silhouettes: Fourier descriptors, shape contexts and Hu moments. An examplebased approach is taken to recover upper body poses from these descriptors. We perform experiments with deformed silhouettes to test each descriptor’s robustness against variations in body dimensions, viewpoint and noise. It is shown that Fourier descriptors and shape context histograms outperform Hu moments for all deformations.
    Original languageUndefined
    Title of host publicationProceedings of the IEEE Conference on Automatic Face and Gesture Recognition 2006 (FG 2006)
    Place of PublicationLos Alamitos
    Number of pages6
    ISBN (Print)0-7695-2503-2
    Publication statusPublished - 10 Apr 2006
    Event7th International Conference on Automatic Face and Gesture Recognition, FG 2006 - Southhamton, United Kingdom
    Duration: 10 Apr 200612 Apr 2006
    Conference number: 7

    Publication series

    PublisherIEEE Computer Society Press


    Conference7th International Conference on Automatic Face and Gesture Recognition, FG 2006
    Abbreviated titleFG
    Country/TerritoryUnited Kingdom
    Internet address


    • METIS-238153
    • EC Grant Agreement nr.: FP6/506811
    • EWI-6866
    • IR-63418

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