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dc.contributor.authorBraunegg, David J.en_US
dc.date.accessioned2004-10-04T14:35:44Z
dc.date.available2004-10-04T14:35:44Z
dc.date.issued1989-09-01en_US
dc.identifier.otherAIM-1184en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/6008
dc.description.abstractThis paper describes a new method for matching, validating, and disambiguating features for stereo vision. It is based on the Marr-Poggio- Grimson stereo matching algorithm which uses zero-crossing contours in difference-of-Gaussian filtered images as features. The matched contours are represented in disparity space, which makes the information needed for matched contour validation and disambiguation easily accessible. The use of disparity space also makes the algorithm conceptually cleaner than previous implementations of the Marr-Poggio-Grimson algorithm and yields a more efficient matching process.en_US
dc.format.extent20 p.en_US
dc.format.extent2933443 bytes
dc.format.extent1118914 bytes
dc.format.mimetypeapplication/postscript
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.relation.ispartofseriesAIM-1184en_US
dc.titleStereo Feature Matching in Disparity Spaceen_US


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