BUILDING ROOF RECONSTRUCTION BY FUSING LASER RANGE DATA AND AERIAL IMAGES

The objective of this study is to present an efficient and robust method of building roof reconstruction by fusing laser range data and aerial images through CSR (Construct-Shape-Refine) procedures. The algorithm starts by extracting 3D line features from laser range data by using the semi-automatic 3D line feature extraction engine. After 3D line features are extracted and regarded as input data for the CSR algorithm, then the procedures of building roof reconstruction are performed in the following algorithms of geometric inferences: (1) constructing the topological relationship of 3D line features that belong to the same building roof by using the special intersecting property of 3D line features projected onto plane; (2) shaping the initial building roof by means of adjusting the 3D line features, and compensating missing parts, if any, by the shortest path algorithm and reporting whether or not the investigated building roof is completed; (3) as a final stage, refining the building roof automatically or semi-automatically by integrating 2D line features observed from the images through geometric inference processes. The experiments show that the proposed CSR algorithm provides a workable platform for building roof reconstruction by fusing laser range data and aerial images. * Corresponding author.