DENSITY-BASED METHOD FOR BUILDING DETECTION FROM LiDAR POINT CLOUD

Abstract

In this paper, a new building detection method based on a density of LIDAR point clouds is proposed. In this method, trees, vegetation, and any objects that have points in a vertical plane or column are removed. In the density-based method, a cube is utilized to calculate the density therein. For each point, the cube is used to determine the number of neighbouring points. The density is calculated in two cases: 3D and 2D space. In 3D space, the volumetric density is calculated using the cube. In 2D space, all points are projected onto the horizontal plane, and the surface density is calculated using a square. Next, the two densities are compared and the points with different values in both cases are removed. The method leads to promising results in the removal of vegetation and trees. Moreover, the results achieve more than 94% completeness and correctness at the per-area level.