The trend in interactive entertainment is towards scenes with massive numbers of characters, and requiring huge amounts of motion data, which must be compactly and efficiently stored without sacrificing quality or controllability of the motions. Multilinear algebra is a powerful tool for efficiently representing multivariate data, including
human motion data, through the analysis of multimodal correlations. The multilinear model, however, often suffers from undesirable artifacts when motion data are sparsely and non-uniformly sampled in a high-dimensional control space. For overcoming this defect, we introduce a geostatistical interpolation to the multilinear model by formulating it to fit into the motion representation with tensor approximation. The advantages of this approach are demonstrated by the motion synthesis in a high-dimensional control space and by a level of detail control. This technique provides practical tools for implementing interactive animations of many characters while ensuring
accurate and flexible controls with a small amount of storage.
雑誌名
Proceedings - SCA 2006 : ACM SIGGRAPH / Eurographics Symposium on Computer Animation 2006, Posters and Demos
ページ
21 - 22
発行年
2006-09
出版者
ACM
権利
(C) ACM 2006. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings – SCA 2006 : ACM SIGGRAPH / Eurographics Symposium on Computer Animation 2006, Posters and Demos, pp.21-22
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sca2006-pd0021
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