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Human Movement Analysis for Interactive Dance

  • Gang Qian
  • Jodi James
  • Todd Ingalls
  • Thanassis Rikakis
  • Stjepan Rajko
  • Yi Wang
  • Daniel Whiteley
  • Feng Guo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4071)

Abstract

In this paper, we provide a brief overview of the human movement analysis research at the Arts, Media and Engineering program, Arizona State University, and its applications in interactive dance. A family of robust algorithms has been developed to analyze dancers’ movement at multiple temporal and spatial levels from a number of perspectives such as marker distributions, joint angles, body silhouettes as well as weight distributions to conduct reliable dancer tracking, posture and gesture recognition. Multiple movement sensing modalities have been used and sometimes fused in our current research, including marker-based motion capture system, pressure sensitive floor and video cameras. Some of the developed algorithms have been successfully used in real life dance performances.

Keywords

Gaussian Mixture Model Motion Capture Gesture Recognition Dynamic Time Warping Motion Capture System 
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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References

  1. 1.
    Guo, F., Qian, G.: Dance Posture Recognition Using Wide-baseline Orthogonal Stereo Cameras. In: Proceedings of IEEE International Conference on Automatic Face and Gesture Recognition (2006)Google Scholar
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    Rajko, S., Qian, G.: A hybrid HMM/DPA adaptive gesture recognition method. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds.) ISVC 2005. LNCS, vol. 3804, pp. 227–234. Springer, Heidelberg (2005)CrossRefGoogle Scholar
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    Wang, Y., Qian, G., Rikakis, T.: Robust Pause Detection Using 3D Motion Capture Data For Interactive Dance. In: Proceedings of International Conference on Acoustics, Speech, and Signal Processing (2005)Google Scholar
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    Whiteley, D., Qian, G., Rikakis, T., James, J., Ingalls, T., Wang, S., Olson, L.: Real-Time Tracking of Multiple People from Unlabelled Markers and Its Application in Interactive Dance. In: Proceedings of British Machine Vision Conference (2005)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Gang Qian
    • 1
    • 2
  • Jodi James
    • 1
  • Todd Ingalls
    • 1
  • Thanassis Rikakis
    • 1
  • Stjepan Rajko
    • 1
    • 3
  • Yi Wang
    • 1
    • 3
  • Daniel Whiteley
    • 1
    • 2
  • Feng Guo
    • 1
    • 2
  1. 1.Arts, Media and Engineering Program 
  2. 2.Department of Electrical Engineering 
  3. 3.Department of Computer Science and EngineeringArizonoa State UniversityTempeUSA

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