Keypose and Style Analysis Based on Low-dimensional Representation

概要

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Human motion analysis is a complex but extremely interesting and important research area in computer graphics and computer vision. This paper addresses three vital topics in human motion analysis related to keyposes: how to extract keyposes from dance motions, how to utilize them, and how to recognize the person and task that constitute a keypose. As our first topic, we propose a new method to extract keyposes from a given dance using the energy flow of the motion. Our experimental results and comparison with a previous keypose extraction approach show the high accuracy of keypose extraction with our new method. As our second topic, we propose a new method to reconstruct low-dimensional motion based on keyposes, and we illustrate the effect of keyposes in a given motion space on human perception. We utilize the keyposes extracted with our new method, formulate a model, and derive a low-dimensional motion based on our model. We also construct low-dimensional motion using uniform sampling poses, and we compare the results with those obtained from our method. As our third topic, we propose a novel approach to decompose motion into common and individual factors using the Multi Factor Tensor (MFT) model. By this method, we recognize person and task from the motion sequence.
一般社団法人情報処理学会の論文
2009-06-02