Abstract
This paper presents a lossy compression method for motion capture data. Each degree of freedom of a motion clip is smoothed by an anisotropic diffusion process and then divided into segments at feature discontinuities. Feature discontinuities are identified by the zero crossings of the second derivative in the smoothed data. Finally, each segment of each degree of freedom is approximated by a cubic Bézier curve. The anisotropic diffusion process retains perceptually important high-frequency parts of the data, including the exact location of discontinuities, while smoothing low-frequency parts of the data. We propose a hierarchical coding method to further compress the cubic control points. We compare our method with wavelet compression methods, which have the best compression rates to date. Experiments show that our method, relative to this work, can achieve about a 65% higher compression rate at the same approximation level.
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Lin, Y., McCool, M.D. (2007). Nonuniform Segment-Based Compression of Motion Capture Data. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2007. Lecture Notes in Computer Science, vol 4841. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76858-6_6
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DOI: https://doi.org/10.1007/978-3-540-76858-6_6
Publisher Name: Springer, Berlin, Heidelberg
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