A Registration Method with Compatibility Distance Ranking for Maximal Clique

High-accuracy point cloud registration is an optimization solution by minimizing the alignment error of feature-metric correspondences. A novel compatibility distance ranking for maximal clique (CDR-MAC) based registration method is proposed for fast and high-accuracy point cloud registration. Based on the graph theory, the correspondences are constructed into graphs of multiple nodes. According to the calculation of edge between two nodes (i.e. compatible correspondences), a fast and valid maximal clique searching method is advanced for accurate transformation estimation, mainly by reserving small percentage of the correspondences after compatibility distance ranking. Extensive experiments on open-source 3DMatch dataset demonstrate that CDR-MAC method achieves the registration of rotation error of 1.50° and translation error of 0.130 m. The runtime of CDR-MAC is less than 2.97 s with an execution time speed-up of one order of magnitude. The method proposed in this work can be applied in the fields of mapping, target recognition and reconstruction.