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    Compression of Human Motion Capture Data Using Motion Pattern Indexing

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    Date
    2009
    Author
    Gu, Qin
    Peng, Jingliang
    Deng, Zhigang
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    Abstract
    In this work, a novel scheme is proposed to compress human motion capture data based on hierarchical structure construction and motion pattern indexing. For a given sequence of 3D motion capture data of human body, the 3D markers are first organized into a hierarchy where each node corresponds to a meaningful part of the human body. Then, the motion sequence corresponding to each body part is coded separately. Based on the observation that there is a high degree of spatial and temporal correlation among the 3D marker positions, we strive to identify motion patterns that form a database for each meaningful body part. Thereafter, a sequence of motion capture data can be efficiently represented as a series of motion pattern indices. As a result, higher compression ratio has been achieved when compared with the prior art, especially for long sequences of motion capture data with repetitive motion styles. Another distinction of this work is that it provides means for flexible and intuitive global and local distortion controls.
    BibTeX
    @article {10.1111:j.1467-8659.2008.01309.x,
    journal = {Computer Graphics Forum},
    title = {{Compression of Human Motion Capture Data Using Motion Pattern Indexing}},
    author = {Gu, Qin and Peng, Jingliang and Deng, Zhigang},
    year = {2009},
    publisher = {The Eurographics Association and Blackwell Publishing Ltd},
    ISSN = {1467-8659},
    DOI = {10.1111/j.1467-8659.2008.01309.x}
    }
    URI
    http://dx.doi.org/10.1111/j.1467-8659.2008.01309.x
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    Eurographics Association copyright © 2013 - 2023 
    Send Feedback | Contact - Imprint | Data Privacy Policy | Disable Google Analytics
    Theme by @mire NV
    System hosted at  Graz University of Technology.
    TUGFhA