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Please use this identifier to cite or link to this item: https://doi.org/10.1109/ICASSP.2005.1416476
DC FieldValue
dc.titleCombining text and audio-visual features in video indexing
dc.contributor.authorChang, S.-F.
dc.contributor.authorManmatha, R.
dc.contributor.authorChua, T.-S.
dc.date.accessioned2013-07-04T08:36:58Z
dc.date.available2013-07-04T08:36:58Z
dc.date.issued2005
dc.identifier.citationChang, S.-F.,Manmatha, R.,Chua, T.-S. (2005). Combining text and audio-visual features in video indexing. ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings V : V1005-V1008. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/ICASSP.2005.1416476" target="_blank">https://doi.org/10.1109/ICASSP.2005.1416476</a>
dc.identifier.isbn0780388747
dc.identifier.issn15206149
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/41835
dc.description.abstractWe discuss the opportunities, state of the art, and open research issues in using multi-modal features in video indexing. Specifically, we focus on how imperfect text data obtained by automatic speech recognition (ASR) may be used to help solve challenging problems, such as story segmentation, concept detection, retrieval, and topic clustering. We review the frameworks and machine learning techniques that are used to fuse the text features with audio-visual features. Case studies showing promising performance will be described, primarily in the broadcast news video domain. © 2005 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/ICASSP.2005.1416476
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1109/ICASSP.2005.1416476
dc.description.sourcetitleICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
dc.description.volumeV
dc.description.pageV1005-V1008
dc.description.codenIPROD
dc.identifier.isiutNOT_IN_WOS
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