Abstract
This paper addresses the problem of real-time location of the joints or centres of rotation (CoR) of human skeletons in the presence of missing data. The data is assumed to be 3d marker positions from a motion capture system. We present an integrated framework which predicts the occluded marker positions using a Kalman filter in combination with inferred information from neighbouring markers and thereby maintains a continuous data-flow. The CoR positions can be calculated with high accuracy even in cases where markers are occluded for a long period of time.
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Aristidou, A., Cameron, J., Lasenby, J. (2008). Predicting Missing Markers to Drive Real-Time Centre of Rotation Estimation. In: Perales, F.J., Fisher, R.B. (eds) Articulated Motion and Deformable Objects. AMDO 2008. Lecture Notes in Computer Science, vol 5098. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-70517-8_23
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DOI: https://doi.org/10.1007/978-3-540-70517-8_23
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-70516-1
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