Feature filtering in relevance feedback of image retrieval based on a statistical approach

Fu, H; Chi, ZG; Feng, DD

doi:10.1109/ISIMP.2004.1434147

Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1894

DC Field	Value	Language
dc.contributor	Department of Electronic and Information Engineering	-
dc.creator	Fu, H	-
dc.creator	Chi, ZG	-
dc.creator	Feng, DD	-
dc.date.accessioned	2014-12-11T08:26:45Z	-
dc.date.available	2014-12-11T08:26:45Z	-
dc.identifier.isbn	0-7803-8687-6	-
dc.identifier.uri	http://hdl.handle.net/10397/1894	-
dc.language.iso	en	en_US
dc.publisher	IEEE	en_US
dc.rights	© 2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.	en_US
dc.rights	This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.	en_US
dc.subject	Content-based retrieval	en_US
dc.subject	Feature extraction	en_US
dc.subject	Filtering theory	en_US
dc.subject	Image retrieval	en_US
dc.subject	Image sampling	en_US
dc.subject	Relevance feedback	en_US
dc.subject	Statistical analysis	en_US
dc.title	Feature filtering in relevance feedback of image retrieval based on a statistical approach	en_US
dc.type	Conference Paper	en_US
dc.description.otherinformation	Author name used in this publication: Zheru Chi	en_US
dc.description.otherinformation	Author name used in this publication: Dagan Feng	en_US
dc.description.otherinformation	Centre for Multimedia Signal Processing, Department of Electronic and Information Engineering	en_US
dc.description.otherinformation	Refereed conference paper	en_US
dc.identifier.doi	10.1109/ISIMP.2004.1434147	-
dcterms.abstract	Relevance feedback is a powerful tool to grasp the user's intention in image retrieval systems and has attracted many researchers' attention since 90's. In this paper, a feature filter whose parameters are computed by a statistical re-sampling approach is proposed in order to select the unique features to characterize the positive samples. A statistical voting procedure is then adopted to rank the candidates after getting rid of irrelevant feature components. Experimental results show that the proposed approach is more efficient and robust than the traditional method.	-
dcterms.accessRights	open access	en_US
dcterms.bibliographicCitation	ISIMP 2004 : proceedings of 2004 International Symposium on Intelligent Multimedia, Video and Speech Processing : October 20-22, 2004, Hong Kong, p. 647-650	-
dcterms.issued	2004	-
dc.identifier.isi	WOS:000227714000162	-
dc.identifier.scopus	2-s2.0-14544280986	-
dc.identifier.rosgroupid	r25185	-
dc.description.ros	2004-2005 > Academic research: refereed > Refereed conference paper	-
dc.description.oa	Version of Record	en_US
dc.identifier.FolderNumber	OA_IR/PIRA	en_US
dc.description.pubStatus	Published	en_US
Appears in Collections:	Conference Paper

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