Detecting and Matching Repeated Patterns for Automatic Geo-tagging in Urban Environments, Grant Schindler, P. Krishnamurthy, R. Lublinerman, Y. Liu, and Frank Dellaert, IEEE Comp. Soc. Conf. on Computer Vision and Pattern Recognition (CVPR), 2008.

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.