Building Detection from High Resolution Colour

We describe a new method for the detection and reconstruction of building in dense urban areas using high resolution aerial images. Our approach begins with the generation of a dense digital elevation model (DEM). A sparse disparity map is densiied using a region-based segmentation of the left aerial image: each detected region is tested to be planar in the disparity map. A strategy is proposed to optimize the generation of these planar surfaces taking into account the noise present in the sparse disparity map and the robustness and complexity of diierent algorithms for planar approximation. The second step of our approach deals with the generation of building hypotheses. Based on the DEM previously computed, geometric and colorimetric criteria are used for the fusion of parallel regions, for the detection of symmetrical regions in the 3D object space and for the reconstruction of roof buildings. Experimental results are presented on a scene in the suburb of Bruxelles with colour images at the resolution of 10cm/pixel.