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Communication dans un congrès

Dominant and Complementary Multi-Emotional Facial Expression Recognition Using C-Support Vector Classification

Abstract : We are proposing a new facial expression recognition model which introduces 30+ detailed facial expressions recognisable by any artificial intelligence interacting with a human. Throughout this research, we introduce two categories for the emotions, namely, dominant emotions and complementary emotions. In this research paper the complementary emotion is recognised by using the eye region if the dominant emotion is angry, fearful or sad, and if the dominant emotion is disgust or happiness the complementary emotion is mainly conveyed by the mouth. In order to verify the tagged dominant and complementary emotions, randomly chosen people voted for the recognised multi-emotional facial expressions. The average results of voting are showing that 73.88% of the voters agree on the correctness of the recognised multi-emotional facial expressions.
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Communication dans un congrès
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https://hal.univ-angers.fr/hal-02528740
Contributeur : Okina Université d'Angers <>
Soumis le : mercredi 1 avril 2020 - 23:41:04
Dernière modification le : jeudi 2 avril 2020 - 10:15:39

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Christer Loob, Pejman Rasti, Iiris Lüsi, Julio Jacques Junior, Xavier Baró, et al.. Dominant and Complementary Multi-Emotional Facial Expression Recognition Using C-Support Vector Classification. 2017 12th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2017), 2017, Washington, United States. pp.833-838, ⟨10.1109/FG.2017.106⟩. ⟨hal-02528740⟩

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