Abstract
This paper proposes a keyframe extraction method based on a novel layered curve simplification algorithm for motion capture data. Bone angles are employed as motion features and keyframe candidates can be selected based on them. After that, the layered curve simplification algorithm will be used to refine those candidates and the keyframe collection can be gained. To meet different requirements for compression and level of detail of motion abstraction, adaptive extraction parameters are also applied. The experiments demonstrate that our method can not only compress and summarize the motion capture data efficiently, but also keep the consistency of keyframe collection between similar human motion sequences, which is of great benefit to further motion data retrieval or editing.
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Xiao, J., Zhuang, Y., Yang, T., Wu, F. (2006). An Efficient Keyframe Extraction from Motion Capture Data. In: Nishita, T., Peng, Q., Seidel, HP. (eds) Advances in Computer Graphics. CGI 2006. Lecture Notes in Computer Science, vol 4035. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11784203_44
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DOI: https://doi.org/10.1007/11784203_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-35638-7
Online ISBN: 978-3-540-35639-4
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