Automating Expressive Locomotion Generation

title="Automating Expressive Locomotion Generation",
journal="Transactions on Edutainment VII",
author="Yejin Kim AND Michael Neff ",
keywords="Character animation, Locomotion style, Motion transition, Motion path, Motion capture data",
volume="LNCS 7145",
location="Chengdu, China",
eventtime="May, 2011",
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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