Integration of Image Data for Refining Building Boundaries Derived from Point Clouds

Abstract. Geometrically and topologically correct 3D building models are required to satisfy with new demands such as 3D cadastre, map updating, and decision making. More attention on building reconstruction has been paid using Airborne Laser Scanning (ALS) point cloud data. The planimetric accuracy of roof outlines, including step-edges is questionable in building models derived from only point clouds. This paper presents a new approach for the detection of accurate building boundaries by merging point clouds acquired by ALS and aerial photographs. It comprises two major parts: reconstruction of initial roof models from point clouds only, and refinement of their boundaries. A shortest closed circle (graph) analysis method is employed to generate building models in the first step. Having the advantages of high reliability, this method provides reconstruction without prior knowledge of primitive building types even when complex height jumps and various types of building roof are available. The accurate position of boundaries of the initial models is determined by the integration of the edges extracted from aerial photographs. In this process, scene constraints defined based on the initial roof models are introduced as the initial roof models are representing explicit unambiguous geometries about the scene. Experiments were conducted using the ISPRS benchmark test data. Based on test results, we show that the proposed approach can reconstruct 3D building models with higher geometrical (planimetry and vertical) and topological accuracy.