Rooftop Detection and 3D Building Modeling from Aerial Images

  • Fanhuai Shi
  • Yongjian Xi
  • Xiaoling Li
  • Ye Duan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5876)


This paper presents a new procedure for rooftop detection and 3D building modeling from aerial images. After an over-segmentation of the aerial image, the rooftop regions are coarsely detected by employing multi-scale SIFT-like features and visual object recognition. In order to refine the detected result and remove the non-rooftop regions, we further resort to explore the 3D information of the rooftop by 3D reconstruction. Wherein, we employ a hierarchical strategy to obtain the corner correspondence between images based on an asymmetry correlation corner matching. We determine whether a candidate region is a rooftop or not according to its height information relative to the ground plane. Finally, the 3D building model with texture mapping based on one of the images is given. Experimental results are shown on real aerial scenes.


Ground Plane Corner Point Image Block Aerial Image Texture Mapping 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Fanhuai Shi
    • 1
    • 2
  • Yongjian Xi
    • 1
  • Xiaoling Li
    • 1
  • Ye Duan
    • 1
  1. 1.Computer Science DepartmentUniversity of Missouri-ColumbiaUSA
  2. 2.Welding Engineering InstituteShanghai Jiao Tong UniversityChina

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