Geometric refinement of laser-derived building roof contours using photogrammetric data

Abstract

In this paper, a methodology is proposed for the geometric refinement of laser scanning building roof contours using high-resolution aerial images and Markov Random Field (MRF) models. The proposed methodology takes for granted that the
3D description of each building roof reconstructed from the laser scanning data (i.e., a polyhedron) is topologically correct and that it is only necessary to improve its accuracy. Since roof ridges are accurately extracted from laser scanning data, our main objective is to use high-resolution aerial images to improve the accuracy of
roof outlines. In order to meet this goal, the available roof contours are first projected onto the image-space. After that,  the projected polygons and the straight lines extracted from the image are used to establish an MRF description, which is based on relations (relative length, proximity, and orientation) between the two sets of straight lines. The energy function associated with the MRF is minimized by using a modified version of the brute force algorithm, resulting in the grouping of straight lines for each roof object. Finally, each grouping of straight lines is topologically reconstructed based on the topology of the corresponding laser
scanning polygon projected onto the image-space. The preliminary results showed that the proposed methodology is promising, since most sides of the refined polygons are geometrically better than corresponding projected laser scanning straight lines.