Fusion of terrestrial laser scanner data and images for building reconstruction

The increasing need and use of 3D GIS particularly in urban areas has produced growing attention on building reconstruction, which attempts to generate geometric and radiometric models of buildings usually from sensory data. The popular data used for building reconstruction are traditionally aerial or satellite images, more recently airborne LIDAR data, or the combination of these data. Extensive studies on building reconstruction from these data have developed some competitive algorithms with reasonable performance and some degree of automation. Nevertheless, the level of details and completeness of the reconstructed building models often cannot reach the high standards that is now or will be required by 3D GIS in future. Hence, the use of close-range data that can provide higher resolution and more complete coverage has been intensively emphasized. The representative close-range sensors are digital cameras and terrestrial laser scanners providing images and points, respectively. We attempted to develop a fusion approach for building reconstruction from both points and images. The proposed approach was then applied to reconstructing a building model from real data sets acquired from a large complex existing building. Based on the experimental results, we assured that the proposed approach cam achieve high resolution and accuracy in building reconstruction. The proposed approach can effectively contribute in developing an operational system producing large urban models for 3D GIS with reasonable resources.