Automatic 3d motion synthesis with time-striding hidden markov model

Authors:
Yi Wang;Zhi-qiang Liu;Li-zhu Zhou
Affiliations:
Department of Computer Science and Technology, Tsinghua University, Graduate School at Shenzhen, China;School of Creative Media, City University of Hong Kong, Hong Kong, China;Department of Computer Science and Technology, Tsinghua University, Graduate School at Shenzhen, China
Venue:
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Year:
2005

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Abstract

In this paper we present a new method, time-striding hidden Markov model (TSHMM), to learn from long-term motion for atomic behaviors and the statistical dependencies among them. TSHMM is a 2-layer hidden Markov model, which approximates a variable-length hidden Markov model by first-order statistical dependencies. An EM algorithm is proposed to learn the TSHMM.