Curvature-based segmental sampling for point cloud registration

Abstract

Point cloud registration is an important part of point cloud processing. An unsuitable down sampling filter in registration can lead to inaccurate registration results. In this paper, a Curvature-Based Segmental Sampling (CBSS) method is proposed, which arranges the curvatures of vertices in descending order and then divides them into many segments, and finally selects the vertices with higher curvature as the sampling results. The algorithm is implemented with the open-source library Point Cloud Library (PCL) and then the filter is compared with Voxel Grid (VG) and Normal Space Sampling (NSS) through a series of registration experiments. The experimental results demonstrate that the proposed filter outperforms the other two filters in achieving higher coarse registration accuracy.