Abstract: The key step of non-rigid human reconstruction is the non-rigid registration of 3D point clouds. This article focuses on the non-rigid registration method of point clouds. 3D human registration is divided into processing of original depth images, corresponding point estimation, and point cloud registration. This article uses bilateral filtering to remove noise from the depth image, extracts the human part by the threshold method, applies the vector field consensus algorithm to estimate the corresponding point and builds a normal vector consistency regular terms based registration model based on the embedded deformation model. The results of test show this article’s method accelerates the iteration rate in point cloud registration and improves the accuracy of point cloud registration, so that demonstrates the advantages of this articles method of registration.

Key words: point cloud non-rigid registration, correspondence point estimation, vector field consistency, embedded deformation, image processing