AUTOMATIC REMOVAL OF NOISE IN POINT CLOUD DATA USING STATISTICAL AND GEOMETRIC

Abstract

 In recent years, advances in satellite positioning technology and the widespread use and sophistication of mobile information terminals such as smartphones are expected to lead to the realization of a society with a high-precision positioning environment (high-precision positioning society). Narabe et al. conducted a 3D point cloud measurement experiment using an indoor MMS, and created a 3D model for indoor navigation. However, the simplification of point cloud processing and modeling work remained an issue. Therefore, in this study, assuming that the 3D model of indoor environment is generated from the point cloud acquired using a walking MMS, we evaluated and discussed the automatic removal of noise in the acquired point cloud and the method to simplify the work of generating 3D data from point cloud data.