Building contour regularization method based on ground LIDAR point cloud data

摘要

Ground laser LIDAR can obtain complete and dense building facade point cloud data, Based on such data, this paper presents a complete regularization method of building contour. Different facades can be regularized, including facade walls, doors and Windows, etc. First, 2D α-shape algorithm is used to roughly extract contour, then the contour of the plane is classified by Euclidean distance clustering, The RANSAC algorithm combined with the least square method is used to extract the line segments for each small class of contour lines, The extracted line segment is modeled according to the main direction of the building, and set a certain distance threshold. The points greater than the distance threshold are removed. The remaining points are adjusted in coordinates according to the model to achieve the effect of regularization. Finally, the regularized point clouds of each small segment are merged to obtain the regularized contour of the final facade. The experiments show that the method in this paper can achieve good regularization effect of building contour. The research results have a certain reference significance for building 3D modeling using ground laser scanning data.