Movie Emotion Estimation with Multimodal Fusion and Synthetic Data Generation

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dc.authorid0000-0001-6342-428X
dc.authorscopusid57197808186
dc.authorscopusid36241785000
dc.authorscopusid7006556254
dc.authorwosidSalah, Albert Ali/ABH-5561-2020
dc.contributor.authorKarslıoğlu, Nihan
dc.contributor.authorKaya, Heysem
dc.contributor.authorSalah, Albert Ali
dc.date.accessioned2022-05-11T14:15:55Z
dc.date.available2022-05-11T14:15:55Z
dc.date.issued2019
dc.departmentFakülteler, Çorlu Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description27th Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2019 -- Sivas Cumhuriyet Univ, Sivas, TURKEY
dc.description.abstractIn this work, we propose a method for automatic emotion recognition from movie clips. This problem has applications in indexing and retrieval of large movie and video collections, summarization of visual content, selection of emotion-invoking materials, and such. Our approach aims to estimate valence and arousal values automatically. We extract audio and visual features, summarize them via functionals, PCA, and Fisher vector encoding approaches. We used feature selection based on canonical correlation analysis. For classification, we used extreme learning machine and support vector machine. We tested our approach on the LIRIS-ACCEDE database with ground truth annotations. The class imbalance problem was solved by generating synthetic data. By fusing the best features at score and feature level, we obtain good results on this problem, especially for the valence prediction.
dc.description.sponsorshipIEEE Turkey Sect, Turkcell, Turkhavacilik Uzaysanayii, Turitak Bilgem, Gebze Teknik Univ, SAP, Detaysoft, NETAS, Havelsan
dc.identifier.isbn978-1-7281-1904-5
dc.identifier.issn2165-0608
dc.identifier.scopus2-s2.0-85071983371
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.11776/6121
dc.identifier.wosWOS:000518994300126
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorKaya, Heysem
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2019 27th Signal Processing and Communications Applications Conference (Siu)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectMovie analysis
dc.subjectaffective computing
dc.subjectmultimodal fusion
dc.subjectRepresentation
dc.titleMovie Emotion Estimation with Multimodal Fusion and Synthetic Data Generation
dc.title.alternativeFilmlerde Otomatik Duygu Analizi için Sentetik Veri Üretimi ve Çokkipli Birleştirme]
dc.typeConference Object

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