Face Identification by a Cascade of Rejection Classifiers


Show simple item record Yuan, Quan en_US Thangali, Ashwin en_US Sclaroff, Stan en_US 2011-10-20T05:22:57Z 2011-10-20T05:22:57Z 2005-06-10 en_US
dc.description.abstract Nearest 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.sponsorship National Science Foundation (EIA-0202067, IIS-0329009); Office of Naval Research (N00014-03-1-0108) en_US
dc.language.iso en_US en_US
dc.publisher Boston University Computer Science Department en_US
dc.relation.ispartofseries BUCS Technical Reports;BUCS-TR-2005-022 en_US
dc.title Face Identification by a Cascade of Rejection Classifiers en_US
dc.type Technical Report en_US

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