“A real-time sequential algorithm for human joint localization” by Cameron and Lasenby

  • ©Jonathan Cameron and Joan Lasenby




    A real-time sequential algorithm for human joint localization



    Locating the CoRs from optical MoCap data is important in both computer graphics and rehabilitation medicine. It is a crucial step in acquiring a skeleton from raw motion capture data. Previous methods suffer from optimization steps which grow with the amount of data supplied [Gamage and Lasenby 2002; Kirk et al. 2005] and both a lack of enforcement of rigid body constraints and the necessity of user feedback to set marker weights [Silaghi et al. 1998]. Here we consider a formulation of the problem that takes full advantage of the simplification that all markers on a body segment are attached to a rigid body. The following formulation uses geometric algebra to simplify understanding and implementation.


    1. Gamage, S. H. U., and Lasenby, J. 2002. New least squares solutions for estimating the average centre of rotation and the axis of rotation. Journal of Biomechanics 35, 87–93.]]
    2. Kirk, A., O’Brien, J., and Forsyth, D. 2005. Skeletal parameter estimation from optical motion capture data. In Proceedings of CVPR.]]
    3. Silaghi, M., Plänkers, R., Boulic, R., Fua, P., and Thalmann, D. 1998. Local and global skeleton fitting techniques for optical motion capture. In Proceedings CapTech.]]

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