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dc.contributor.authorYuan, Quanen_US
dc.contributor.authorThangali, Ashwinen_US
dc.contributor.authorSclaroff, Stanen_US
dc.date.accessioned2011-10-20T05:22:57Z
dc.date.available2011-10-20T05:22:57Z
dc.date.issued2005-06-10en_US
dc.identifier.urihttp://hdl.handle.net/2144/1848
dc.description.abstractNearest neighbor search is commonly employed in face recognition but it does not scale well to large dataset sizes. A strategy to combine rejection classifiers into a cascade for face identification is proposed in this paper. A rejection classifier for a pair of classes is defined to reject at least one of the classes with high confidence. These rejection classifiers are able to share discriminants in feature space and at the same time have high confidence in the rejection decision. In the face identification problem, it is possible that a pair of known individual faces are very dissimilar. It is very unlikely that both of them are close to an unknown face in the feature space. Hence, only one of them needs to be considered. Using a cascade structure of rejection classifiers, the scope of nearest neighbor search can be reduced significantly. Experiments on Face Recognition Grand Challenge (FRGC) version 1 data demonstrate that the proposed method achieves significant speed up and an accuracy comparable with the brute force Nearest Neighbor method. In addition, a graph cut based clustering technique is employed to demonstrate that the pairwise separability of these rejection classifiers is capable of semantic grouping.en_US
dc.description.sponsorshipNational Science Foundation (EIA-0202067, IIS-0329009); Office of Naval Research (N00014-03-1-0108)en_US
dc.language.isoen_USen_US
dc.publisherBoston University Computer Science Departmenten_US
dc.relation.ispartofseriesBUCS Technical Reports;BUCS-TR-2005-022en_US
dc.titleFace Identification by a Cascade of Rejection Classifiersen_US
dc.typeTechnical Reporten_US


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