Variable duration motion texture for human motion modeling

Authors:
Tianyu Huang;Fengxia Li;Shouyi Zhan;Jianyuan Min
Affiliations:
School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China;School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China;School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China;School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China
Venue:
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Year:
2006

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Abstract

Statistical model is an effective method for character motion modeling. In this paper, a variable duration motion texture is proposed to represent complex human motion that is statistically similar to the original captured motion data. The motion texture is defined as a threelevel structure with moton abstracts, motons and their distribution. The motion texture is modeled by a Semi-SLDS (Semi- Switching Linear Dynamic System), which provides an intuitive framework for describing the continuous but nonlinear dynamics of human motion. To explicitly incorporate duration modeling capability, the Semi-SLDS is adopted to improve SLDS by replacing the Markov switching layer with semi-Markov model. In addition, the proposed approach is proved flexible and effective by several motion applications, namely motion synthesis, motion recognition and motion compression.