Reconstructing 3d Buildings from Lidar Data

Accurate 3D surface models in urban areas are essential for a variety of applications, such as visualization, GIS, and mobile communications. Since manual surface reconstruction is very costly and time consuming, the development of automated algorithms is of great importance. On the other hand LIDAR data is a relatively new technology for obtaining Digital Surface Models (DSM) of the earth’s surface. It is a fast method for sampling the earth’s surface with a high density and high point accuracy. In this paper a new approach for building extraction from LIDAR data is presented. The approach utilizes the geometric properties of urban buildings for the reconstruction of the building wire-frames from the LIDAR data. We start by finding the candidate building points that are used to populate a plane parameter space. After filling the plane parameter space, we find the planes that can represent the building roof surfaces. Roof regions are then extracted and the plane parameters are refined using a robust estimation technique and the geometric constraint between adjacent roof facets. The region boundaries are extracted and used to form the building wireframes. The algorithm is tested on two buildings from a locally acquired LIDAR data sets. The test results show some success in extracting urban area buildings.