Automatic Generation of High-Quality Three-Dimensional Urban Buildings from Aerial Images

摘要

High-quality three-dimensional building databases are essential inputs for urban area geographic information systems. Because manual generation of these databases is extremely costly and time-consuming, the development of automated algorithms is greatly needed. This article presents a new algorithm to automatically extract accurate and reliable three-dimensional building information. High overlapping aerial images are used as input to the algorithm. Radiometric and geometric properties of buildings are utilized to distinguish building roof regions in the images. This is accomplished with image segmentation and neural network techniques. A rule-based system is employed to extract the vertices of the roof polygons in all images. Photogrammetric mathematical models are used to generate the roof topology and compute the three-dimensional coordinates of the roof vertices. The algorithm is tested on 30 buildings in a complex urban scene. Results showed that 95 percent of the building roofs are extracted correctly. The root-mean-square error for the extracted building vertices is 0.35 meter using 1:4000 scale aerial photographs scanned at 30 microns.