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Automatic extraction of generic house roofs from high resolution aerial imagery

Part of the Lecture Notes in Computer Science book series (LNCS,volume 1064)

Abstract

We present a technique to extract complex suburban roofs from sets of aerial images. Because we combine 2-D edge information, photometric and chromatic attributes and 3-D information, we can deal with complex houses. Neither do we assume the roofs to be flat or rectilinear nor do we require parameterized building models. From only one image, 2-D edges and their corresponding attributes and relations are extracted. Using a segment stereo matching based on all available images, the 3-D location of these edges are computed. The 3-D segments are then grouped into planes and 2-D enclosures are extracted, thereby allowing to infer adjoining 3-D patches describing roofs of houses. To achieve this, we have developed a hierarchical procedure that effectively pools the information while keeping the combinatorics under control. Of particular importance is the tight coupling of 2-D and 3-D analysis.

Keywords

  • Digital Terrain Model
  • Aerial Image
  • Automatic Extraction
  • Epipolar Line
  • Infinite Plane

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.

We acknowledge the support given to this research by ETH under project 13-1993-4.

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© 1996 Springer-Verlag Berlin Heidelberg

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Bignone, F., Henricsson, O., Fua, P., Stricker, M. (1996). Automatic extraction of generic house roofs from high resolution aerial imagery. In: Buxton, B., Cipolla, R. (eds) Computer Vision — ECCV '96. ECCV 1996. Lecture Notes in Computer Science, vol 1064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0015525

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  • DOI: https://doi.org/10.1007/BFb0015525

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