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Published in:
2005 | OriginalPaper | Chapter
Motion Normalization
Authors : Yan Gao, Lizhuang Ma, Zhihua Chen, Xiaomao Wu
Published in: Affective Computing and Intelligent Interaction
Publisher: Springer Berlin Heidelberg
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This paper presents a very simple but efficient algorithm to normalize all motion data in database with same skeleton length. The input motion stream is processed sequentially while the computation for a single frame at each step requires only the results from the previous step over a neighborhood of nearby backward frames. In contrast to previous motion retargeting approaches, we simplify the constraint condition of retargeting problem, which leads to the simpler solutions. Moreover, we improve Shin et al.’s algorithm [10], which is adopted by a widely used Kovar’s footskate cleanup algorithm [6] through adding one case missed by it.