Point Cloud Registration Algorithm Based on Overlapping Region Extraction

Abstract

During the process of the point cloud registration, the problem that the accuracy is not high is due to the unknown relative position of the multi-view point clouds and the diversity of the target structure. This paper proposes a point cloud registration method based on extracting overlapping regions to solve it. First of all, according to the characteristics of the target geometric structure, each point cloud is divided into blocks and the ESF multi-dimensional shape descriptors of each point cloud block are constructed, the region with the greatest similarity between the descriptors, namely the overlapping region between the point clouds. Then our algorithm uses the Super Four Point Fast Robust Matching (Super4PCS) algorithm to execute a coarse registration of point clouds in overlapping regions, the initial positions of the point clouds after the coarse registration are obtained according to the consistency constraints, and finally uses the iterative closest point algorithm (ICP) to precisely register the overlapping region and obtain the final point cloud model. Compared with traditional Super4PCS algorithm, the experimental results show that the method proposed in this paper effectively improves the accuracy and accelerates the process of point cloud registration.