DocumentCode :
3220273
Title :
Segmentation of complex buildings from aerial images and 3D surface reconstruction
Author :
Cohen, Laurent D. ; Vinson, Samuel
Author_Institution :
CEREMADE, Univ. Paris 9 Dauphine, France
fYear :
2002
fDate :
2002
Firstpage :
215
Lastpage :
219
Abstract :
This paper presents a new method for extraction of buildings in aerial images. We first present a method based on rectangular buildings, which are the most common constructions. We then extend this method to more complex shapes by decomposition in a set of rectangles. These rectangles are used to enhance a 3D reconstruction of the digital elevation model (DEM). Based on stereo data, we use the DEM and the orthoimage for a first segmentation of all areas at elevation above ground. We estimate the rectangle parameters over any given blob and define a criterion for checking the similarity between shape and model. We introduce a new approach for automatic reconstruction of buildings of complex shapes using an iterative splitting of the region until it is covered by a set of rectangles. This automatic process is successfully illustrated on synthetic and real examples. In order to refine location and size of the model, we present a deformable rectangle template. The final rectangle and complex shape models are used together with elevation to obtain a 3D realistic reconstruction of the scene including building models.
Keywords :
architecture; feature extraction; image reconstruction; image segmentation; 3D reconstruction; aerial images; automatic reconstruction; deformable rectangle template; digital elevation model; extraction of buildings; geographic site 3D reconstruction; iterative splitting; segmentation; structure extraction; Buildings; Deformable models; Digital elevation models; Image reconstruction; Image segmentation; Iterative methods; Layout; Parameter estimation; Shape; Surface reconstruction;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applications of Computer Vision, 2002. (WACV 2002). Proceedings. Sixth IEEE Workshop on
Print_ISBN :
0-7695-1858-3
Type :
conf
DOI :
10.1109/ACV.2002.1182184
Filename :
1182184
Link To Document :
بازگشت