Method of segmentation and semi-automatic modeling for vehicle-borne LiDAR point cloud data

Abstract

A method of segmentation and semi- automated modeling for vehicle- borne light detection and ranging( LiDAR) point cloud data is presented in this paper. Firstly,the LiDAR point cloud data are converted into standard format and sampled sparsely. Then the geometric features of different objects are used to govern the data and model of 3D roads,buildings,trees,power poles and facilities. In view of the imperfection of vehicle- borne LiDAR point cloud data,the vehicle- borne and texture information of aerial image auxiliary is used to build the facade and the top surface of the three- dimensional modeling. Finally,a streetscape is reconstructed by using IP-S2 vehicle- borne LiDAR point cloud data. The results show that the method proposed in this paper is simple and suitable for semi- automatic segmentation of roads and buildings.