DocumentCode :
3637099
Title :
Building reconstruction using manhattan-world grammars
Author :
Carlos A. Vanegas;Daniel G. Aliaga;Bedřich Beneš
Author_Institution :
Purdue University
fYear :
2010
fDate :
6/1/2010 12:00:00 AM
Firstpage :
358
Lastpage :
365
Abstract :
We present a passive computer vision method that exploits existing mapping and navigation databases in order to automatically create 3D building models. Our method defines a grammar for representing changes in building geometry that approximately follow the Manhattan-world assumption which states there is a predominance of three mutually orthogonal directions in the scene. By using multiple calibrated aerial images, we extend previous Manhattan-world methods to robustly produce a single, coherent, complete geometric model of a building with partial textures. Our method uses an optimization to discover a 3D building geometry that produces the same set of façade orientation changes observed in the captured images. We have applied our method to several real-world buildings and have analyzed our approach using synthetic buildings.
Keywords :
"Geometry","Image reconstruction","Computer vision","Navigation","Image databases","Spatial databases","Layout","Robustness","Solid modeling","Optimization methods"
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on
ISSN :
1063-6919
Print_ISBN :
978-1-4244-6984-0
Type :
conf
DOI :
10.1109/CVPR.2010.5540190
Filename :
5540190
Link To Document :
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