ISCAS OpenIR
tracking end-effectors for marker-less 3d human motion estimation in multi-view image sequences
Wang Wenzhong; Wang Zhaoqi; Deng Xiaoming; Luo Bin
2013
Conference Name15th International Conference on Human-Computer Interaction, HCI International 2013
SourceLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages227-235
Conference DateJuly 21, 2013 - July 26, 2013
Conference PlaceLas Vegas, NV, United states
Indexed TypeEI
ISSN0302-9743
ISBN9783642393419
Department(1) Computer Science Department Anhui University China; (2) Institute of Computing Technology Chinese Academy of Sciences China; (3) Institute of Software Chinese Academy of Sciences China
English AbstractWe propose to track the end-effectors of human body, and use them as kinematic constraints for reliable marker-less 3D human motion tracking. In the presented approach, we track the end-effectors using particle filtering. The tracked results are then combined with image features for 3D full pose tracking. Experimental results verified that the inclusion of end-effectors' constraints improves the tracking performances. © 2013 Springer-Verlag.; We propose to track the end-effectors of human body, and use them as kinematic constraints for reliable marker-less 3D human motion tracking. In the presented approach, we track the end-effectors using particle filtering. The tracked results are then combined with image features for 3D full pose tracking. Experimental results verified that the inclusion of end-effectors' constraints improves the tracking performances. © 2013 Springer-Verlag.
KeywordHuman Computer Interaction Monte Carlo Methods Signal Filtering And Prediction Target Tracking
Language英语
Content Type会议论文
URIhttp://ir.iscas.ac.cn/handle/311060/15971
Collection中国科学院软件研究所
Recommended Citation
GB/T 7714
Wang Wenzhong,Wang Zhaoqi,Deng Xiaoming,et al. tracking end-effectors for marker-less 3d human motion estimation in multi-view image sequences[C],2013:227-235.
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