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Wide baseline correspondence extraction beyond local features

By Ruan Lakemond, Sridha Sridharan and Clinton B. Fookes


Robust, affine covariant, feature extractors provide a means to extract correspondences between images captured by widely separated cameras. Advances in wide baseline correspondence extraction require looking beyond the robust feature extraction and matching approach. This study examines new techniques of extracting correspondences that take advantage of information contained in affine feature matches. Methods of improving the accuracy of a set of putative matches, eliminating incorrect matches and extracting large numbers of additional correspondences are explored. It is assumed that knowledge of the camera geometry is not available and not immediately recoverable. The new techniques are evaluated by means of an epipolar geometry estimation task. It is shown that these methods enable the computation of camera geometry in many cases where existing feature extractors cannot produce sufficient numbers of accurate correspondences

Topics: 010299 Applied Mathematics not elsewhere classified, cameras, feature extraction, affine features, image matching, geometry
Publisher: The Institute of Engineering Technology
Year: 2011
DOI identifier: 10.1049/iet-cvi.2010.0045
OAI identifier:

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