目的 人手结构估测是建立个性化3维人手模型以及进行人手姿态估测的重要步骤之一。由于人手骨架为表皮所覆盖，普通摄像机无法直接获得其结构，因此常常需要人员参与估测过程，无法真正实现自动化，这必然会增加估测的时间和估测的复杂度。方法 本文从人手纹理与人手关节位置相关性出发，利用一套图像分割和图像增强技术提取出大致的人手连接结构；再利用多视点3维建模、3维拟合技术和粒子群优化算法，优化之前得到的人手连接结构。结果 经实验证明该方法能成功地提取出人手结构，估测的每个阶段均无需人员参与。结论 与之前方法相比，该方法真正实现了估测过程自动化，减少了估测时间和估测误差。

Objective Calibration of hand structures is one of important steps to create an individualized three-dimensional hand model and estimate hand-pose. Because the hand structure is covered by the hand surface, the common cameras cannot directly get the hand structure, and people were required to participate in the calibration of hand structure, which cannot be completely processed by the computer. That makes the calibration complex and more time is needed. Method In order to acquire an automatic calibration of a hand structure, a set of image segmentation and enhancement techniques were used to find the link structure of the hand, based on the relationship of hand prints and joints in the individual's hand. The techniques of 3D modeling using multiple cameras, 3D fitting, and the Particle Swarm Optimization algorithm were used to optimize the link structure of hand. Result Proved by the experiments, the calibration method proposed in this paper can successfully extract the structure of the hand, and each stage of the calibration process doesn't need people participating in. Conclusion Comparing with the original method, the calibration method proposed in this paper is completed by the computer. As a result the calibration time is saved and errors are reduced.