Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-17829-0_44
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dc.titleMulti-actor emotion recognition in movies using a bimodal approach
dc.contributor.authorSrivastava, R.
dc.contributor.authorRoy, S.
dc.contributor.authorYan, S.
dc.contributor.authorSim, T.
dc.date.accessioned2013-07-23T09:30:19Z
dc.date.available2013-07-23T09:30:19Z
dc.date.issued2011
dc.identifier.citationSrivastava, R.,Roy, S.,Yan, S.,Sim, T. (2011). Multi-actor emotion recognition in movies using a bimodal approach. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6524 LNCS (PART 2) : 465-475. ScholarBank@NUS Repository. <a href="https://doi.org/10.1007/978-3-642-17829-0_44" target="_blank">https://doi.org/10.1007/978-3-642-17829-0_44</a>
dc.identifier.isbn3642178286
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/43298
dc.description.abstractApproaches for emotion recognition in movie scenes using high level features, consider emotion of only a single actor. The contribution of this paper is to analyze using emotional information from multiple actors present in the scene instead of just one actor. A bimodal approach is proposed for fusing emotional cues from different actors using two different fusion methods. Emotional cues are obtained from facial expressions and dialogs. Experimental observations show that emotions of other actors do not necessarily provide helpful information about the emotion of the scene and recognition accuracy is better when emotions of only the speaker are considered. © 2011 Springer-Verlag Berlin Heidelberg.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/978-3-642-17829-0_44
dc.sourceScopus
dc.subjectbimodal
dc.subjectemotion recognition
dc.subjectHuman Computer Interface
dc.subjectmovie analysis
dc.subjectSemantic Orientation
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1007/978-3-642-17829-0_44
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume6524 LNCS
dc.description.issuePART 2
dc.description.page465-475
dc.identifier.isiutNOT_IN_WOS
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