Title:
Detecting and Matching Repeated Patterns for Automatic Geo-tagging in Urban Environments
Detecting and Matching Repeated Patterns for Automatic Geo-tagging in Urban Environments
Author(s)
Schindler, Grant
Krishnamurthy, Panchapagesan
Lublinerman, Roberto
Liu, Yanxi
Dellaert, Frank
Krishnamurthy, Panchapagesan
Lublinerman, Roberto
Liu, Yanxi
Dellaert, Frank
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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.
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Date Issued
2008-06
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Text
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Post-print
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