Feature Selection for Face Detection

Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/7232

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DC Field	Value	Language
dc.creator	Serre, Thomas	-
dc.creator	Heisele, Bernd	-
dc.creator	Mukherjee, Sayan	-
dc.creator	Poggio, Tomaso	-
dc.date	2004-10-20T21:03:34Z	-
dc.date	2004-10-20T21:03:34Z	-
dc.date	2000-09-01	-
dc.date.accessioned	2013-10-09T02:48:37Z	-
dc.date.available	2013-10-09T02:48:37Z	-
dc.date.issued	2013-10-09	-
dc.identifier	AIM-1697	-
dc.identifier	CBCL-192	-
dc.identifier	http://hdl.handle.net/1721.1/7232	-
dc.identifier.uri	http://koha.mediu.edu.my:8181/xmlui/handle/1721	-
dc.description	We present a new method to select features for a face detection system using Support Vector Machines (SVMs). In the first step we reduce the dimensionality of the input space by projecting the data into a subset of eigenvectors. The dimension of the subset is determined by a classification criterion based on minimizing a bound on the expected error probability of an SVM. In the second step we select features from the SVM feature space by removing those that have low contributions to the decision function of the SVM.	-
dc.format	7211022 bytes	-
dc.format	1034240 bytes	-
dc.format	application/postscript	-
dc.format	application/pdf	-
dc.language	en_US	-
dc.relation	AIM-1697	-
dc.relation	CBCL-192	-
dc.title	Feature Selection for Face Detection	-
Appears in Collections:	MIT Items

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