【摘要】 通过对状态预报误差的协方差矩阵的各个分量分别进行控制,设计一种强跟踪扩展卡尔曼跟踪滤波器,并在单目相机环境下利用该滤波器对3D人手运动过程中的突变状态进行跟踪;讨论了3D人手生理模型、运动模型等问题;最后通过大量实验证明了该强跟踪滤波器的有效性.与现有的STEKF滤波器相比,文中的强跟踪滤波器具有更强的跟踪能力.更多还原

【Abstract】 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 in [6],our algorithm manifests superiority of tracking abrupt changing states.更多还原