A Strong Tracking Extended Kalman Filter and Its Applications in Moving Human Hand Tracking

By controlling independently each components of the error covariance matrix,a new strong tracking extended Kalman filter(STEKF) is put forward which can effectively track the abruptly changing states of a moving human hand with a single camera.Besides,the design of 3D physiological models and kinematic models of the tracked hand are also discussed.At last,several experiments validate the proposed filter.Compared with the STEKF proposed in6,our algorithm manifests superiority of tracking abrupt changing states.