Regularity-Driven Facade Matching Between Aerial and Street Views

Mark Wolff, Robert T. Collins, Yanxi Liu; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, pp. 1591-1600

Abstract


We present an approach for detecting and matching building facades between aerial view and street-view images. We exploit the regularity of urban scene facades as captured by their lattice structures and deduced from median-tiles' shape context, color, texture and spatial similarities. Our experimental results demonstrate effective matching of oblique and partially-occluded facades between aerial and ground views. Quantitative comparisons for automated urban scene facade matching from three cities show superior performance of our method over baseline SIFT, Root-SIFT and the more sophisticated Scale-Selective Self-Similarity and Binary Coherent Edge descriptors. We also illustrate regularity-based applications of occlusion removal from street views and higher-resolution texture-replacement in aerial views.

Related Material


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[bibtex]
@InProceedings{Wolff_2016_CVPR,
author = {Wolff, Mark and Collins, Robert T. and Liu, Yanxi},
title = {Regularity-Driven Facade Matching Between Aerial and Street Views},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2016}
}