Dynamic hand shape manifold embedding and tracking from depth maps
ACCV'12 Proceedings of the 11th international conference on Computer Vision - Volume 2
Computer Vision and Image Understanding
Joint view-identity manifold for infrared target tracking and recognition
Computer Vision and Image Understanding
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This paper presents a new approach for hand rotation and grasping tracking from a single IR camera. For the complexity and ambiguity of hand pose, it is difficult to track hand pose and view variations simultaneously from a single camera. We propose a cylindrical manifold embedding for one dimensional hand pose variation and cyclic viewpoint variation. A hand pose shape from a specific viewpoint can be generated from an embedding point on the cylindrical manifold after learning nonlinear generative models from the embedding space to the corresponding observed shape. Hand grasping with simultaneous hand rotation is tracked using particle filter on the manifold space. Experimental results for synthetic and real data show accurate tracking of grasping hand with rotation. The proposed approach shows potentials for advanced user interface in dark environments.