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A group of novel approaches and a toolkit for motion capture data reusing

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Abstract

Now more and more motion capture (MoCap) systems are used to acquire realistic and highly detailed motion data which are widely used for producing animations of human-like characters in a variety of applications, such as simulations, video games and animation films. And recently large MoCap databases are available. As a kind of emerging multimedia data, 3D human motion has its own specific data form and standard format. But to the best of our knowledge, only a few approaches have been explored for 3D MoCap data feature representation and reusing. This paper proposes a group of novel approaches for posture feature representation, motion sequence segmentation, key-frame extraction and content-based motion retrieval, which are all very important for MoCap data reusing and benefit to the efficient animation production. To validate these approaches, we set up a MoCap database and implemented a prototype toolkit. The experiments show that the proposed algorithms could achieve the approvable results.

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Acknowledgement

This work is supported by the National Natural Science Foundation of China under Grant No.60525108; the National Key Technology R&D Program of China under Grant No.2007BAH11B00; the Program for Changjiang Scholars and Innovative Research Team in University under grant No. IRT0652; the National Science Foundation for Post-doctoral Scientists of China under Grant No. 20080431327.

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Authors and Affiliations

  1. Institute of Artificial Intelligence, Zhejiang University, Hangzhou, 310027, China

    Jun Xiao, Yueting Zhuang, Fei Wu, Tongqiang Guo & Zhang Liang

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  1. Jun Xiao
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  2. Yueting Zhuang
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  3. Fei Wu
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  4. Tongqiang Guo
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  5. Zhang Liang
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Correspondence to Jun Xiao.

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Xiao, J., Zhuang, Y., Wu, F. et al. A group of novel approaches and a toolkit for motion capture data reusing. Multimed Tools Appl 47, 379–408 (2010). https://doi.org/10.1007/s11042-009-0329-1

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