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An Efficient Keyframe Extraction from Motion Capture Data

  • Jun Xiao
  • Yueting Zhuang
  • Tao Yang
  • Fei Wu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4035)

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.

Keywords

Compression Ratio Human Motion Motion Sequence Motion Capture Data Original Motion 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jun Xiao
    • 1
  • Yueting Zhuang
    • 1
  • Tao Yang
    • 1
  • Fei Wu
    • 1
  1. 1.Institute of Artificial IntelligenceZhejiang UniversityHangzhouP.R. China

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