Abstract
This paper describes a method to analyze human motion, based on the reduction of multidimensional captured motion data. A Dynamic Programming Piecewise Linear Approximation model is used to automatically extract in an optimal way key-postures distributed along the motion data. This non uniform sub-sampling can be exploited for motion compression, segmentation, or re-synthesis. It has been applied on arm end-point motion for 3D or 6D trajectories. The analysis method is then evaluated, using an approximation of the curvature and the tangential velocity, which turns out to be robust to noise and can be calculated on multidimensional data.
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Gibet, S., Marteau, PF. (2008). Analysis of Human Motion, Based on the Reduction of Multidimensional Captured Data – Application to Hand Gesture Compression, Segmentation and Synthesis. 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_8
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DOI: https://doi.org/10.1007/978-3-540-70517-8_8
Publisher Name: Springer, Berlin, Heidelberg
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