Building 3D Model Reconstruction Method Based on Airborne LiDAR Point Cloud Data
Taking airborne LiDAR point cloud data as the research object,this paper proposes a set of 3D building model reconstruc-tion methods. Firstly,the progressive TIN filtering algorithm is used to classify the ground points and non-ground points,and the building point cloud is extracted through the trained random forest model;secondly,taking the direction as the constraint condition,we use Random Sample Consensus (RANSAC) algorithm to extract the building contour and obtain the key points of the roof;finally,the SharpGL toolkit is used to reconstruct the 3D models of the buildings based on the building contour and roof key point information. Taking the actual airborne LiDAR point cloud data as an example,the experimental results show that the method in this paper can ex-tract the complete building contour information,and has high building model reconstruction accuracy.
万方数据
维普
