Inferring 3D Layout of Building Facades From a Single Image

Jiyan Pan, Martial Hebert, Takeo Kanade; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 2918-2926

Abstract


In this paper, we propose a novel algorithm that infers the 3D layout of building facades from a single 2D image of an urban scene. Different from existing methods that only yield coarse orientation labels or qualitative block approximations, our algorithm quantitatively reconstructs building facades in 3D space using a set of planes mutually related by 3D geometric constraints. Each plane is characterized by a continuous orientation vector and a depth distribution. An optimal solution is reached through inter-planar interactions. Due to the quantitative and plane-based nature of our geometric reasoning, our model is more expressive and informative than existing approaches. Experiments show that our method compares competitively with the state of the art on both 2D and 3D measures, while yielding a richer interpretation of the 3D scene behind the image.

Related Material


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[bibtex]
@InProceedings{Pan_2015_CVPR,
author = {Pan, Jiyan and Hebert, Martial and Kanade, Takeo},
title = {Inferring 3D Layout of Building Facades From a Single Image},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}
}