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dc.contributor.authorWang, Bo-Wenen_US
dc.contributor.authorSu, Ja-Hwungen_US
dc.contributor.authorChou, Chien-Lien_US
dc.contributor.authorTseng, Vincent S.en_US
dc.date.accessioned2018-08-21T05:56:42Z-
dc.date.available2018-08-21T05:56:42Z-
dc.date.issued2011-01-01en_US
dc.identifier.issn2376-6816en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TAAI.2011.14en_US
dc.identifier.urihttp://hdl.handle.net/11536/146526-
dc.description.abstractVideo retrieval has been a hot topic due to the prevalence of video capturing devices and media-sharing services such as YouTube. Until now, few past studies has focused on querying the videos by images due to the semantic gap between images and videos is not easy to narrow. To this end, in this paper, we propose a novel semantic video retrieval system that integrates web image annotation and concept matching function to bridge images, concepts and videos. For web image annotation, we exploit textual and visual information in the web image to achieve effective image annotation. For concept matching function, we identify the concept relations by calculating the similarity between two concepts via WordNet. On the basis of web image annotation and concept matching function, the proposed system reaches the goals of usability and intelligence on semantic video retrieval. The experimental results reveal that our proposed system can successfully capture the user's intention between image concepts and video concepts for semantic video retrieval.en_US
dc.language.isoen_USen_US
dc.subjectVideo retrievalen_US
dc.subjectimage annotationen_US
dc.subjectcross media retrievalen_US
dc.subjectquery-by-exampleen_US
dc.titleSemantic Video Retrieval by Integrating Concept- and Content-Aware Miningen_US
dc.typeProceedings Paperen_US
dc.identifier.doi10.1109/TAAI.2011.14en_US
dc.identifier.journal2011 INTERNATIONAL CONFERENCE ON TECHNOLOGIES AND APPLICATIONS OF ARTIFICIAL INTELLIGENCE (TAAI 2011)en_US
dc.citation.spage32en_US
dc.citation.epage37en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000399726900005en_US
Appears in Collections:Conferences Paper