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dc.contributor.authorFu, Hsin C.en_US
dc.contributor.authorXu, Yeong. Y.en_US
dc.contributor.authorPao, Hsiao T.en_US
dc.date.accessioned2014-12-08T15:46:28Z-
dc.date.available2014-12-08T15:46:28Z-
dc.date.issued2008en_US
dc.identifier.isbn978-80-227-2856-0en_US
dc.identifier.urihttp://hdl.handle.net/11536/31275-
dc.description.abstractIn this paper we present a multimodal approach for effectively searching and retrieving images. The proposed multimodal image query and retrieval (MIQR) method uses two or more types of query for accessing images - textual annotation associated with images and visual appearance, such as color, texture and positional features of objects in sample images. A user places a keyword-based query first and then retrieves desired images by visual content-based query. A prototype MIQR system was implemented and is available at hitp://140.113.216.66/WebImageSearch for online demo, and public evaluation. We also conducted experiments over a categorized Corel image collection and a non-categorized WWW image collection to show the performance of the proposed MIQR method.en_US
dc.language.isoen_USen_US
dc.subjectimage query and retrievalen_US
dc.subjecttext searchen_US
dc.subjectmultimodalen_US
dc.subjectcontent based queryen_US
dc.subjectmodel-based searchen_US
dc.titleMultimodal search for effective image retrievalen_US
dc.typeProceedings Paperen_US
dc.identifier.journalPROCEEDINGS OF IWSSIP 2008: 15TH INTERNATIONAL CONFERENCE ON SYSTEMS, SIGNALS AND IMAGE PROCESSINGen_US
dc.citation.spage233en_US
dc.citation.epage236en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000259363700059-
Appears in Collections:Conferences Paper