人体运动跟踪是图像处理和计算机视觉研究的热点问题，它在人机接口、虚拟现实、智能监控、机器人仿真等方面具有广阔应用前景，已引起越来越多学者的关注，为了实现准确的人体运动跟踪，采用了两种基于2－D模型的人体运动跟踪方法：其中，一种方法是以区域面积重合率为区域准则，采用由粗到细的匹配过程，通过建立2－D模型以实现与真实人体运动间的准确匹配；另一种是基于区域特征的2－D模型和人体各个部位的连接关系，通过确定和标记人体的各个部位，最终由2－D模型来重现真实人体的运动过程，同时采用以上两种方法，对实际人体运动进行了跟踪测试，在全身运动的整个过程中能给出较为准确的跟踪结果，表明该方法不仅能抵御噪声和灰度变化的影响，而且能大致估计出被遮挡部位的位置。

Human motion tracking has become a hot issue in the fields of image processing and computer vision. It is receiving increasing attention from more and more researchers due to its wide applications in human-machine interfaces, virtual reality and smart surveillance, robot simulation, etc. In order to track human motion precisely, two methods of automatic tracking are proposed. One method is based on 2-D model. Taking region overlay as the matching criteria, the method adopts a matching procedure from coarse matching to fine matching for establishing the precise correspondence between the 2-D model and real human body motion; the other method is based on the feature of body parts and their connection. By locating the body parts according to their different shapes, the joint connecting the body parts can be located also, and then the human movement can be recovered by 2-D skeleton model. Based on the two methods, real human motion is tracked from simple walking movement to complex gymnastics. The result shows that the method can resist the affection of noise and the variation of intensity, and the position of the overlapped area can be estimated coarsely. Precise result can be acquired in the whole course of the movement of the body.