Manhattan-world Urban Building Reconstruction by Fitting Cubes

He, Zhenbang; Wang, Yunhai; Cheng, Zhanglin

Manhattan-world Urban Building Reconstruction by Fitting Cubes

Files

v40i7pp289-300.pdf (24.5 MB)

Date

2021

Authors

He, Zhenbang
Wang, Yunhai
Cheng, Zhanglin

Publisher

The Eurographics Association and John Wiley & Sons Ltd.

Abstract

The Manhattan-world building is a kind of dominant scene in urban areas. Many existing methods for reconstructing such scenes are either vulnerable to noisy and incomplete data or suffer from high computational complexity. In this paper, we present a novel approach to quickly reconstruct lightweight Manhattan-world urban building models from images. Our key idea is to reconstruct buildings through the salient feature - corners. Given a set of urban building images, Structure-from- Motion and 3D line reconstruction operations are applied first to recover camera poses, sparse point clouds, and line clouds. Then we use orthogonal planes detected from the line cloud to generate corners, which indicate a part of possible buildings. Starting from the corners, we fit cubes to point clouds by optimizing corner parameters and obtain cube representations of corresponding buildings. Finally, a registration step is performed on cube representations to generate more accurate models. Experiment results show that our approach can handle some nasty cases containing noisy and incomplete data, meanwhile, output lightweight polygonal building models with a low time-consuming.

        @article{10.1111:cgf.14421
,
journal = {Computer Graphics Forum},
title = {{Manhattan-world Urban Building Reconstruction by Fitting Cubes
}},
author = {He, Zhenbang and 
Wang, Yunhai and 
Cheng, Zhanglin
},
year = {2021
},
publisher = {The Eurographics Association and John Wiley & Sons Ltd.
},
ISSN = {1467-8659
},
DOI = {10.1111/cgf.14421
}
}