Feature-consistent coplane-pair correspondence- and fusion-based point cloud registration

Abstract

It is an important and challenging task to register two point clouds, and the estimated registration solution can be applied in 3D vision. In this paper, an outlier removal method is first proposed to delete redundant coplane-pair correspondences for constructing three feature-consistent coplane-pair correspondence subsets. Next, Rodrigues’ formula and a scoring-based method are adopted to solve the representative registration solution of each correspondence subset. Then, a robust fusion method is proposed to fuse the three representative solutions as the final registration solution. Based on typical testing datasets, comprehensive experimental results demonstrated that with good registration accuracy, our registration algorithm achieves significant execution time reduction effect when compared with the state-of-the-art methods.