M2DP: A novel 3D point cloud descriptor and its application in loop closure detection

摘要

In this paper, we present a novel global descriptor M2DP for 3D point clouds, and apply it to the problem of loop closure detection. In M2DP, we project a 3D point cloud to multiple 2D planes and generate a density signature for points for each of the planes. We then use the left and right singular vectors of these signatures as the descriptor of the 3D point cloud. Our experimental results show that the proposed algorithm outperforms state-of-the-art global 3D descriptors in both accuracy and efficiency.