A Study on Extraction of Cube Region from 3D Point Cloud Considering Color Distribution in Lab Color Space

Abstract

When creating a three-dimensional point cloud from photographs, a method of creating a three-dimensional point cloud that includes a cube by placing a cube as an indicator in advance is being considered. However, detecting cube regions from a huge amount of point cloud data is computationally expensive. In this study, we propose a method to extract only the cube regions quickly and accurately by a two-step filtering process using the color information assigned to the acquired point cloud, and demonstrate the effectiveness of this method.