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Journal Article Data-Driven Approach for Human Locomotion Generation
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Authors
Yejin Kim, Myunggyu Kim
Issue Date
2015-04
Citation
International Journal of Image and Graphics, v.15, no.2, pp.1-19
ISSN
0219-4678
Publisher
World Scientific
Language
English
Type
Journal Article
DOI
https://dx.doi.org/10.1142/S021946781540001X
Abstract
This paper introduces a data-driven approach for human locomotion generation that takes as input a set of example locomotion clips and a motion path specified by an animator. Significantly, the approach only requires a single example of straight-path locomotion for each style expressed and can produce a continuous output sequence on an arbitrary path. Our approach considers quantitative and qualitative aspects of motion and suggests several techniques to synthesize a convincing output animation: motion path generation, interactive editing, and physical enhancement for the output animation. Initiated with an example clip, this process produces motion that differs stylistically from any in the example set, yet preserves the high quality of the example motion. As shown in the experimental results, our approach provides efficient locomotion generation by editing motion capture clips, especially for a novice animator, at interactive speed.
KSP Keywords
Data-driven approach, Human locomotion, Interactive editing, Motion capture, Motion path, Output sequence, Path generation