Research on 3D building information extraction and image post-processing based on vehicle LIDAR

Abstract

Taking the elevation point cloud data of buildings as an object, this paper proposed a 3D reconstruction method. By using the simple clustering method, the vertices of a plane with similar normal vector components are classified as a set of points on the same plane. The directional clustering method is used to divide each plane point, and the least square method is used to complete the fitting of the data points. The outer boundary of the facade of the building is established, and then the 3D coordinates of each corner point of the elevation are obtained. By constantly changing the threshold of angle limit and iteration number, a maximum slope can be found by choosing the key point. Taking the regular buildings in real blocks as an example, the model is compared with the experimental results. Through comparative analysis experiments, the effectiveness of the proposed method is further demonstrated, and the 3D model of the building can be constructed more accurately.