Detecting and Matching Repeated Patterns for Automatic Geo-tagging in Urban Environments
Conference Paper, Proceedings of (CVPR) Computer Vision and Pattern Recognition, June, 2008
Abstract
We present a novel method for automatically geo-tagging photographs of man-made environments via detection and matching of repeated patterns. Highly repetitive environments introduce numerous correspondence ambiguities and are problematic for traditional wide-baseline matching methods. Our method exploits the highly repetitive nature of urban environments, detecting multiple perspectively distorted periodic 2D patterns in an image and matching them to a 3D database of textured facades by reasoning about the underlying canonical forms of each pattern. Multiple 2D-to-3D pattern correspondences enable robust recovery of camera orientation and location. We demonstrate the success of this method in a large urban environment.
BibTeX
@conference{Schindler-2008-9999,author = {Grant Schindler and Panchapagesan Krishnamurthy and Roberto Lublinerman and Yanxi Liu and Frank Dellaert},
title = {Detecting and Matching Repeated Patterns for Automatic Geo-tagging in Urban Environments},
booktitle = {Proceedings of (CVPR) Computer Vision and Pattern Recognition},
year = {2008},
month = {June},
}
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