Abstract
We propose a novel framework for compressing articulated human motions using multiresolution wavelet techniques. Given a global error tolerance, the number of wavelet coefficients required to represent the motion is minimized. An adaptive error approximation metric is designed so that the optimization process can be accelerated by dynamic programming. The performance is then further improved by choosing wavelet coefficients non-linearly. To handle the footskate artifacts on the contacts, a contact stabilization algorithm which incorporates an Inverse Kinematics solver is adopted. Our framework requires far fewer computations, and achieves better performance in compression ratio compared to the best existing methods.
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Lee, CH., Lasenby, J. (2008). An Efficient Wavelet-Based Framework for Articulated Human Motion Compression. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2008. Lecture Notes in Computer Science, vol 5358. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89639-5_8
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DOI: https://doi.org/10.1007/978-3-540-89639-5_8
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