A Novel Feature Point Detection Algorithm of Unstructured 3D Point Cloud

Abstract

Compared with 3D mesh data, unstructured point cloud data lack adjacency relationship between points, which only contain geometric coordinates and little information. This paper focuses on the research of characteristics of unstructured point cloud detection algorithm. We put forward the multiscale 3D Harris feature point detection algorithm, which uses iteration strategy to select the optimal Harris response value in multiple scales. Compared with the classical 3D Harris feature point detection algorithm for mesh data, our algorithm can fully use the local information of point cloud models to detect feature point on point cloud models. It is very robust to rotation transformation of point clouds and noise.