A Study on Extraction of Cube Region from 3D Point Cloud Considering DoN Features and Color Distribution

Abstract

When creating a three-dimensional point cloud from photographs, a method of creating a three-dimensional point cloud that includes cubes by placing them as indicators in advance has been developed. However, detecting cubes from a huge amount of point cloud data is computationally expensive. In this study, we propose a method to extract only cube regions quickly and accurately by filtering using DoN features calculated from the acquired point cloud and color information and demonstrate the effectiveness of this method.