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Multi-view 3D human pose estimation combining single-frame recovery, temporal integration and model adaptation
2009
2009 IEEE Conference on Computer Vision and Pattern Recognition
We present a system for the estimation of unconstrained 3D human upper body movement from multiple cameras. Its main novelty lies in the integration of three components: single-frame pose recovery, temporal integration and model adaptation. Single-frame pose recovery consists of a hypothesis generation stage, where candidate 3D poses are generated based on hierarchical shape matching in the individual camera views. In the subsequent hypothesis verification stage, candidate 3D poses are
doi:10.1109/cvpr.2009.5206508
dblp:conf/cvpr/HofmannG09
fatcat:ydw46hqxezefdke2t6rgp7zs3u