A new method for registration of 3D point sets with low overlapping ratios

Abstract

The registration of multi-view point sets is often used in surface reconstruction for complex parts, and many researchers are striving to improve its accuracy and efficiency. A popular algorithm for registration of 3D point sets is the Iterative Closest Point (ICP). With the increase of overlapping ratios, the convergence accuracy and speed of ICP algorithm improves. In most cases of 3D scanning systems, the overlapping regions of multi-view point sets often locate at the boundaries. Based on this characteristic, a new method for registration of multi-view point sets with low overlapping ratios is proposed. Firstly, two kinds of sampling strategies are introduced, and a great number of point pairs are constructed. Through surface classification, curvature and neighborhood curvature matching of point pairs, the overlapping regions are selected. Then a Levenberg-Marquardt ICP (LM-ICP) method is used to search optimal registration parameters with the points in the overlapping regions. Finally, experiments for registration of multi-view point sets are performed, and results show that the method can get good registration accuracy for point sets with low overlapping ratios.