Abstract
Technical demands for extraction of significant components from spatial models are increasing as 3D sensor and its application technology had been developed and popularized. Conventional feature extraction for 2D image cannot be applied to depth images analysis, and is not suitable for 3D construction analysis because it extracts gradation between pixel values. In this paper, we proposed a novel method for extraction of characteristic elements from 3D point cloud according to normal vector distribution. In our numerical experiments, characteristics on each point were extracted by the proposed method with robustness to sensing noises, structural holes and irregular density.
