中文摘要：

采用三维人手图模型描述了人手结构、运动学、动力学及自遮挡特性，将人手高维（27维）跟踪问题转为并行跟踪16个6维变量的问题，降低了计算复杂度．在非参数信念传播过程中嵌入连续自适应均值漂移方法得到可行C空间，在该空间中传递消息以提高跟踪效率．实验结果表明，该方法在人手发生自遮挡的情况下，能快速、鲁棒地跟踪关节人手．

英文摘要：

We design a pertinence graphical model, combined with domain-specific heuristics among the components of human hand, to describe the hand＇s 3D structure, kinematics, dynamics and self-occlusion. The modular structure facilitates tracking each hand component （sixteen variables of six degrees of freedom） separately instead of tracking hand configuration of 27 degrees of freedom as a while to reduce the computational complexity. Then, a more efficient belief propagation method embedding continuously adaptive mean shift （CAMSHIFT） algorithm to obtain configuration space （C-space） is proposed. Belief propagation is processed in the feasible C-space to increase the tracking efficiency. The experimental results show that our proposed method can track articulated hand robustly and efficiently under self-occlusion.