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.
Cite
CITATION STYLE
Bignone, F., Henricsson, O., Fua, P., & Stricker, M. (1996). Automatic extraction of generic house roofs from high resolution aerial imagery. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1064, pp. 85–96). Springer Verlag. https://doi.org/10.1007/bfb0015525
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