Building detection from multiple aerial images in dense urban areas

In this paper we present a novel approach for building detection from multiple aerial images in dense urban areas. The approach is based on accurate surface reconstruction, followed by extraction of building fa̧ades that are used as a main cue for building detection. For the fa̧ade detection, a simple but nevertheless flexible and robust algorithm is proposed. It is based on the observation that building façades correspond to the accumulation of 3D data, available from different views, in object space. Knowledge-driven thresholding of 3D data accumulators followed by Hough transform-based segment detection results in the extraction of fa̧ade positions. Three-dimensional planar regions resulting from surface reconstruction procedure and bounded by the extracted fa̧ades are detected as building hypotheses through testing a set of spatial criteria. Then, a set of verification criteria is proposed for the hypothesis confirmation.