Accurate building structure recovery from aerial imagery

Summary form only given, as follows. In this paper, we discuss methods for the detection and reconstruction of buildings from aerial imagery. These methods have been intended for the analysis of urban and suburban areas and have been applied to images of different resolutions (between 1 m and 10 cm per pixel). Various algorithms for image matching have been investigated, including hierarchical processing and new correlation schemes having interesting properties for building recognition and building feature grouping. The cooperative combination of 2D (monocular) and 3D (stereoscopic) information allows the complete representation of the observed scene and particularly the detection of man-made raised structures such as buildings. A performance evaluation on simulation-based images has been considered in comparison with the corresponding ground-truth reference. Our work shows that mid-resolution methods cannot be directly applied to high-resolution images. Classical algorithms have to be adapted and new techniques have been defined to carry out dense urban area reconstruction.