Hand Motion from 3D Point Trajectories and a Smooth Surface Model

A method is proposed to track the full hand motion from 3D points reconstructed using a stereoscopic set of cameras. This approach combines the advantages of methods that use 2D motion (e.g. optical flow), and those that use a 3D reconstruction at each time frame to capture the hand motion. Matching either contours or a 3D reconstruction against a 3D hand model is usually very difficult due to self-occlusions and the locally-cylindrical structure of each phalanx in the model, but our use of 3D point trajectories constrains the motion and overcomes these problems. Our tracking procedure uses both the 3D point matches between two time frames and a smooth surface model of the hand, build with implicit surface. We used animation techniques to represent faithfully the skin motion, especially near joints. Robustness is obtained by using an EM version of the ICP algorithm for matching points between consecutive frames, and the tracked points are then registered to the surface of the hand model. Results are presented on a stereoscopic sequence of a moving hand, and are evaluated using a side view of the sequence.