A Novel 3D Moving Human Hand Tracking Algorithm Based upon Improved Unscented Kalman Filter

A novel moving3D human hand tracking algorithm based on unscented Kalman filter（UKF） is put forward in this paper.In our algorithm,a finger is regarded as a process unit within each loop.Initially,the algorithm predicts states of all joints of a finger using improved UKF algorithm of this paper.The predicted states are used as initial states of a loop process to the finger.Then,re-predicts those joints using the improved UKF algorithm again and again until the differences of all corresponding features between the silhouettes of the image and the projection of the3D predicted virtual hand satisfy the given precision.Existing algorithms have a problem：the tracking precision relies heavily on3D human model.By obtaining the observations of the states,our algorithm resolves the problem.Compared with the relevant algorithms,our algorithm can more effectively deal with hand self-occlusion issues,and is more robust to 3D human hand models as well.