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dc.contributor.authorChang, FCen_US
dc.contributor.authorHang, HMen_US
dc.date.accessioned2014-12-08T15:25:17Z-
dc.date.available2014-12-08T15:25:17Z-
dc.date.issued2005en_US
dc.identifier.isbn0-8194-5655-1en_US
dc.identifier.issn0277-786Xen_US
dc.identifier.urihttp://hdl.handle.net/11536/17652-
dc.identifier.urihttp://dx.doi.org/10.1117/12.586678en_US
dc.description.abstractContent-based image search has long been considered a difficult task. Making correct conjectures on the user intention (perception) based on the query images is a critical step in the content-based search. One key concept in this paper is how we find the user preferred image characteristics from the multiple positive samples provided by the user. The second key concept is that when the user does not provide a sufficient number of samples, how we generate a set of consistent "pseudo images". The notion of image feature stability is thus introduced. The third key concept is how we use negative images as pruning criterion. In realizing the preceding concepts, an image search scheme is developed using the weighted low-level image features. At the end, quantitative simulation results are used to show the effectiveness of these concepts.en_US
dc.language.isoen_USen_US
dc.subjectimage retrievalen_US
dc.subjectperception weightingen_US
dc.titleA relevance feedback image retrieval scheme using multi-instance and pseudo image conceptsen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1117/12.586678en_US
dc.identifier.journalSTORAGE AND RETRIEVAL METHODS AND APPLICATIONS FOR MULTIMEDIA 2005en_US
dc.citation.volume5682en_US
dc.citation.spage224en_US
dc.citation.epage235en_US
dc.contributor.department電子工程學系及電子研究所zh_TW
dc.contributor.departmentDepartment of Electronics Engineering and Institute of Electronicsen_US
dc.identifier.wosnumberWOS:000228758500022-
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