Detection and modeling of buildings from multiple aerial images

Abstract

Automatic detection and description of cultural features, such as buildings, from aerial images is becoming increasingly important for a number of applications. This task also offers an excellent domain for studying the general problems of scene segmentation, 3D inference, and shape description under highly challenging conditions. We describe a system that detects and constructs 3D models for rectilinear buildings with either flat or symmetric gable roofs from multiple aerial images; the multiple images, however, need not be stereo pairs (i.e., they may be acquired at different times). Hypotheses for rectangular roof components are generated by grouping lines in the images hierarchically; the hypotheses are verified by searching for presence of predicted walls and shadows. The hypothesis generation process combines the tasks of hierarchical grouping with matching at successive stages. Overlap and containment relations between 3D structures are analyzed to resolve conflicts. This system has been tested on a large number of real examples with good results, some of which are included in the paper along with their evaluations.