3D rooftop extraction using perceptual organization based on fast graph search

This paper presents a new building rooftop extraction method from aerial images. In our approach, we extract the useful building location information from the generated disparity map to segment the interested objects and consequently reduce unnecessary line segments extracted in low level feature extraction step. Hypothesis selection is carried out by using undirected graph, in which close cycles represent complete rooftops hypotheses. We test the proposed method with the synthetic images generated from Avenches dataset of Ascona aerial images. The experiment result shows that the extracted 3D line segments of the reconstructed buildings reflect the actual building structure and our method can be efficiently used for the task of building detection and reconstruction from aerial images.