1998
DOI: 10.1007/bfb0055681
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Automatic modelling and 3D reconstruction of urban house roofs from high resolution aerial imagery

Abstract: Many tasks in modern urban planning require 3-dimensional (3D) spatial information, preferably in the form of 3D city models. Constructing such models requires automatic methods for reliable 3D building reconstruction. House roofs encountered in residential areas in European cities exhibit a wide variety in their shapes. This limits the use of predefined roof models for their reconstruction. The strategy put forward in this paper is, first, to construct a polyhedral model of the roof structure, which captures … Show more

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Cited by 40 publications
(24 citation statements)
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References 14 publications
(22 reference statements)
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“…• A detailed image model [4,41,30,[42][43][44] with rich attributes and a feature adjacency graph exploits much better the information contained in the image. Especially for matching in more than one image, the probability can be raised significantly, compared to approaches based only on one feature type (mostly edges).…”
Section: Modelmentioning
confidence: 99%
“…• A detailed image model [4,41,30,[42][43][44] with rich attributes and a feature adjacency graph exploits much better the information contained in the image. Especially for matching in more than one image, the probability can be raised significantly, compared to approaches based only on one feature type (mostly edges).…”
Section: Modelmentioning
confidence: 99%
“…Using 2D image data only, Moons et al [4] proposed a method to reconstruct 3D polyhedral models. This method requires that accurate camera model information is readily available.…”
Section: Related Workmentioning
confidence: 99%
“…The approach in [11] is also relevant but assumes the existence of multiple interconnected line segments to detect endpoints, information which is not available in our case. In contrast to [12], we cannot assume a short baseline as the user may be performing rapid motions. We do not employ stereo [13], as it yields inaccuracies on thin objects.…”
Section: Related Workmentioning
confidence: 99%