A Registration Method on Piece-wise Voting for Low Overlapping 3D Point Clouds

Abstract

To date, there is a wide range of registration methods for 3D point clouds. Nevertheless, most approaches are inadequate for pairs of 3D point clouds with low overlapping ratios due to many incorrect estimates of putative point correspondences when numerous outliers are present. In this particular scenario, points from the non-overlapping areas represent the outliers. In this work, we introduce a piecewise voting-based method that leverages the repeatability of the transformation matrices that result from registering point subsets of the overlapping areas. We show the performance of our approach under the effect of its ruling parameters through extensive ablation experiments to define an easy-to-follow usage guideline and compare it to available state-of-the-art registration methods for low overlap 3D points clouds.