深度图像匹配在三维数字成像与造型、三维光学检测领域中，具有重要的作用及研究价值。其匹配精度的高低、速度的快慢直接影响到最终三维模型的测量精度与速度。目前应用较为广泛的匹配方法主要有基于迭代最近点和基于标志点两种方法。简要论述了各种深度图像匹配的方法，着重介绍迭代最近点与借助标志点两种方法的理论与发展，并结合实验数据，阐述两种方法优缺点、匹配精度、误差来源、时间复杂度、应用前景等。

Registration of range images plays a key role in 3D digital imaging and modeling and 3D optical inspection. Its precision and velocity directly determine the quality of 3D model construction. At present, two registration methods, iterative closest points and markers, are in wide application. All kinds of methods for range images registration are summarized, where iterative closest points method and markers method are introduced mainly. According to experimental results, these two methods are compared in various regions, including registration-error, registration-time, error-source, application-areas and so on.