From LIDAR Point Clouds to 3D Building Models

High quality and dense sampling are two major properties of recent airborne LIDAR data which are still improving. In this thesis a novel approach for generating 3D building models from LIDAR data is presented. It consists of four major parts: filtering of non-ground regions, segmentation and classification, building outline approximation, and 3D modeling. With filtering non-ground structures are eliminated from the laser data. Image reconstruction by means of geodesic morphology is at the core of the proposed algorithm. Structures which do not comply concerning size, or shape are suppressed. By interpolating the bald earth produced by filtering, Digital Terrain Models (DTM) are generated. Image segmentation creates the potential non-ground regions which are subject to rule-based classification. Geometric feature descriptors based on surface normals, the local height variation, and a vegetation index are employed to classify data into buildings, trees, and other objects such as power lines and cranes. After building classification, their outlines are extracted and unnecessary points are eliminated by two approximation procedures. One fits rectilinear polygons to the building outlines by a hierarchical adaptation of Minimum Bounding Rectangles (MBR). This works fast and reliable, but is restricted to rectangular shapes. For non-rectangular polygons, a Random Sample Consensus (RANSAC) based procedure is employed to fit straight lines. Lines are then intersected or joined. The automatic generation of 3D building models follows the definitions of the Levels of Detail (LOD) in the CityGML standard. Three LOD are considered in this thesis. The first LOD (LOD0) consists of the extracted DTM from the LIDAR data. A prismatic model containing the major walls of the building forms the LOD1. For it, the building roof is approximated by a horizontal plane. LOD2 includes the roof structures into the model. A model driven approach based on the analysis of the 3D points in 2D projection planes is proposed to analyze the roof structure. Building regions are divided into smaller parts according to the direction and the number of ridge lines, the latter extracted using geodesic morphology. A 3D model is derived for each building part. Finally, a complete building model is formed by merging the 3D models of the building parts and adjusting the nodes after merging. Results for test data show the potential but also the shortcomings of the approach also in comparison to related work