Optimized initial aligning algorithm for point cloud registration

This paper deals with the initial aligning problem of pairwise point cloud registration. A novel Distance Disparity Matrix algorithm derived from Euclidean invariants of rigid motion is proposed to prune the obvious outlier matches while keeping the most inliers.The pruned matches are then sent into a Least-Squares Backward procedure to estimate optimized rigid transformation in fewer iterations.The employed thresholds are automatically determined with respect to the actual resolution of input point clouds. Experimental results show that the proposed strategy effectively eliminates the outliers to achieve better initial alignment at a high speed, and further enhances the performance of point cloud registration.