This paper presents a knowledge-based approach for automatic 3D reconstruction of buildings from aerial images. By combining the image analysis with information from GIS maps and specific knowledge of the buildings the complexity of the building reconstruction task can be greatly reduced. The building reconstruction process is described as a tree search in the space of possible building hypotheses. Hypotheses derived from outlines of building footprints from the map are fit against image pixel gradients. To guide the search of the tree an evaluation function based on information theory principles is defined. The proposed evaluation function defines the score of matching between a hypothesised building model and the image pixel gradients. It uses a mutual information measure and MDL criterion to select the best fit to image data in the tree search.
['Ildiko Suveg', 'George Vosselman']
3D Building Reconstruction by Map Based Generation and Evaluation of Hypotheses.