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Local pose prior based 3D Human motion capture from depth camera

SU Le 1,2  CHAI Jin-Xiang 3  XIA Shi-Hong 1

1 (Beijing Key Lab of Mobile Computing and Pervasive Devices, Advanced Computing Research Laboratory, Institute Of Computing Technology Chinese Academy Of Sciences, Beijing, 100190, China) 
2 (University of Chinese Academy of Sciences, Beijing, 100049, China) 
3 (Texas A&M University, Computer Science and Engineering, Texas 77843-3112, USA))

This paper introduces a local pose prior based real-time online approach to capture 3D human animation from a single depth camera. The key idea is to learn a series of local pose prior models with K motion capture examples from a pre-established large and heterogeneous human motion database, according to automatically extracted labelled virtual sparse 3D markers from captured depth image. Then, by solving a Maximum A Posterior (MAP) problem via an iteratively optimization process, the system automatically tracks the 3D human motion sequence. The experiments show that, the proposed approach robustly captures accurate 3 D human motions at 25fps. The proposed tracking system can easily applied to different actors with large different body sizes via an automatically indi vidual body parameters calibration process. The proposed system can widely apply to 3D game/movie produce, human-machine interaction.

Local pose prior based 3D Human motion capture from depth camera. Journal of software, 2016.(China Computer Graphics Conference 2016,Best Paper Award) [ Paper 1,735KB] [ Slides 1,577KB] [ Video 189,220KB]