Most motion tracking algorithms rely on an initial skeleton model that has already been fitted to a special posture setup. However, such a first identification of markers often requires multiple manual actions of a designer. To automate this process, a novel approach for adapting a basic skeleton model to empirical motion capture data is presented. The approach is based on the anthropometric dimensions of a subject and subsequent tree-based skeleton fitting. It generates a tree representation of different possible skeleton configurations. The tree is annotated with costs based on discrepancies between markers and anatomic landmarks. A computation of the least cost path through the tree automatically results in an optimal fitting of the observed markers to the given anthropometric data of the subject.


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    Title :

    Enhancing Motion Capture Performance by Means of an Internal Anthropometric Skeleton Model


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    Digital Human Modeling for Design and Engineering Symposium ; 2008



    Publication date :

    2008-06-17




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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