Representability of human motions by factorial hidden Markov models

@article{Kulic2007RepresentabilityOH,
  title={Representability of human motions by factorial hidden Markov models},
  author={Dana Kulic and Wataru Takano and Yoshihiko Nakamura},
  journal={2007 IEEE/RSJ International Conference on Intelligent Robots and Systems},
  year={2007},
  pages={2388-2393}
}
This paper describes an improved methodology for human motion recognition and imitation based on factorial hidden Markov models (FHMM). Unlike conventional hidden Markov models (HMMs), FHMMs use a distributed state representation, which allows for more efficient representation of each time sequence. Once the FHMMs are trained with exemplar motion data, they can be used to generate sample trajectories for motion production, and produce significantly more accurate trajectories compared to single… CONTINUE READING
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Stochastic segmentation, proto-symbol coding and clustering of motion patterns and their application to signifiant communication between man and humanoid robot

  • W. Takano
  • Ph.D. dissertation, University of Tokyo, 2006.
  • 2006
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