Epitomic Analysis of Human Motion
نویسندگان
چکیده
This paper introduces a novel epitomic model for motion capture data which we call the motion epitome. Epitomic motion analysis results in a generative time series model which compresses sequences of motion capture data into a compact representation of their most salient constituent elements. In comparison to conventional generative models of human motion such as a Hidden Markov Model or Switching Linear Dynamic System, the motion epitome offers the potential to simultaneously represent correlations at multiple time scales and complex patterns of dependency between states in the model. Used in conjunction with nonparametric motion representations (such as motion graphs [2]), the motion epitome offers the potential to generate more accurate transitions between motion sequences.
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