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Recognizing Induced Emotions of Movie Audiences: Are Induced and Perceived Emotions the Same?

Tian, Leimin
Lai, Catherine
Moore, Johanna D.
Year 2017
Abstract Predicting the emotional response of movie audiences to affective movie content is a challenging task in affective computing. Previous work has focused on using audiovisual movie content to predict movie induced emotions. However, the relationship between the audience’s perceptions of the affective movie content (perceived emotions) and the emotions evoked in the audience (induced emotions) remains unexplored. In this work, we address the relationship between perceived and induced emotions in movies, and identify features and modelling approaches effective for predicting movie induced emotions. First, we extend the LIRIS-ACCEDE database by annotating perceived emotions in a crowd-sourced manner, and find that perceived and induced emotions are not always consistent. Second, we show that dialogue events and aesthetic highlights are effective predictors of movie induced emotions. In addition to movie based features, we also study physiological and behavioural measurements of audiences. Our experiments show that induced emotion recognition can benefit from including temporal context and from including multimodal information. Our study bridges the gap between affective content analysis and induced emotion prediction.
Keywords Emotion recognitionAffectMultimodal learning
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Proceedings (Author postprint) (441 Kb) - public document Free access
Research groups Computer Vision and Multimedia Laboratory
Multimodal Interaction Group
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TIAN, Leimin et al. Recognizing Induced Emotions of Movie Audiences: Are Induced and Perceived Emotions the Same?. [s.l.] : [s.n.], 2017. https://archive-ouverte.unige.ch/unige:101281

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Deposited on : 2018-01-09

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