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| Title | Automating Expressive Locomotion Generation
(Article) |
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| in | Transactions on Edutainment VII |
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| Author(s) |
Yejin Kim, Michael Neff |
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| Keyword(s) | Character animation, Locomotion style, Motion transition, Motion path, Motion capture data |
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| Year |
2012
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| Location | Chengdu, China |
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| Date | May, 2011 |
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| Volume | LNCS 7145 |
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| Publisher | Springer |
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| Pages | 48--61 |
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| Abstract |
This paper introduces a system for expressive locomotion generation that takes as input a set of sample locomotion clips and a motion path. Significantly, the system only requires a single sample of straight-path locomotion for each style modeled and can produce output locomotion for an arbitrary path with arbitrary motion transition points. For efficient locomotion generation, we represent each sample with a loop sequence which encapsulates its key style and utilize these sequences throughout the synthesis process. Several techniques are applied to automate the synthesis: foot-plant detection from unlabeled samples, estimation of an adaptive blending length for a natural style change, and a post-processing step for enhancing the physical realism of the output animation. Compared to previous approaches, the system requires significantly less data and manual labor, while supporting a large range of styles.
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