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abstract

Analysis of dance movements using gaussian processes: extended abstract

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Published:29 October 2012Publication History

ABSTRACT

This work addresses the Huawei/3DLife Grand Challenge, presenting a novel method for the analysis of dance movements. The approach focuses on the decomposition of the dance movements into elementary motions. Placing this problem into a probabilistic framework, we propose to exploit Gaussian processes to accurately model the different components of the decomposition. The preliminary results, presented in this paper, are very promising. In particular, two applications are considered, illustrating the relevance of the proposed approach, namely the correction of tracking errors and the smoothing of some movements of the teacher to help toward the dance learning.

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References

  1. http://3dlife-huawei-gc-submission.blogspot.fr/.Google ScholarGoogle Scholar
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  5. C. E. Rasmussen and C. K. I. Williams. Gaussian Processes for Machine Learning (Adaptive Computation and Machine Learning). The MIT Press, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library

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