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Object pose estimation by manifold learning has become a hot research area recently. In this paper, we propose an efficient method that can recover pose and viewpoints for numerous hand gestures from monocular videos based on Locality Preserving Projections. We first select some hand dynamic gestures as primitive hand motions and set a 3D-2D mapping table to relate 3D joint angles of sampling static...
This paper presents a general framework that can efficiently recover intrinsic hand configurations and viewpoints based on "multi-view and continuous motion" manifold learnt by LLP (Locality Preserving Projections) from monocular video. Firstly, 3D information of joint angels for a gesture with its 2D projecting silhouettes from multi-viewpoints is related via a 3D-2D mapping table offline...
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