Point registration is a critical step of three-dimensional modeling, but the registration rate has been a major bottleneck restricting development of point registration. In the real life, the point registration data are large in scale and have certain requirement of the registration rate. Concerning decrease of the registration rate resulted from a large point registration scale and potential registration failure caused by a too large cloud distance, this paper combines features of curvature and the concept of coherent point drift to propose a quick point registration method. To begin with, the point cloud curvature is calculated. Then, the curvature similarity between point clouds is compared. The registered point clouds with feature points similar in the structure are extracted. This experiment suggests that this method can not only reduce the time consumption of registration by around two folds, but also register point clouds within the distance of 200 units of coordinate difference.