A Local Approach for Negative Emotion Detection
Document type :
Communication dans un congrès avec actes
Title :
A Local Approach for Negative Emotion Detection
Author(s) :
Lablack, Adel [Auteur]
FOX MIIRE [LIFL]
Danisman, Taner [Auteur]
FOX MIIRE [LIFL]
Bilasco, Ioan Marius [Auteur]
Université de Lille, Sciences et Technologies
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
FOX MIIRE [LIFL]
Djeraba, Chaabane [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Institut de Recherche sur les Composants logiciels et matériels pour l'Information et la Communication Avancée - UAR 3380 [IRCICA]
FOX MIIRE [LIFL]
FOX MIIRE [LIFL]
Danisman, Taner [Auteur]
FOX MIIRE [LIFL]
Bilasco, Ioan Marius [Auteur]
Université de Lille, Sciences et Technologies
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
FOX MIIRE [LIFL]
Djeraba, Chaabane [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Institut de Recherche sur les Composants logiciels et matériels pour l'Information et la Communication Avancée - UAR 3380 [IRCICA]
FOX MIIRE [LIFL]
Conference title :
International Conference on Pattern Recognition
City :
Stockholm
Country :
Suède
Start date of the conference :
2014-08-24
Publication date :
2014-08-25
HAL domain(s) :
Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
English abstract : [en]
Recognizing human facial expression and emotion by computer is an interesting and challenging problem. In this paper, we propose a method for recognizing negative emotions through an appropriate representation of facial ...
Show more >Recognizing human facial expression and emotion by computer is an interesting and challenging problem. In this paper, we propose a method for recognizing negative emotions through an appropriate representation of facial features from relevant face regions displayed in video streams and still images. A measure that is sensitive to facial movements is used in predefined regions of interest to detect the negative emotions. The experimentation has been performed on a standard dataset and live video streams and has showed promising results.Show less >
Show more >Recognizing human facial expression and emotion by computer is an interesting and challenging problem. In this paper, we propose a method for recognizing negative emotions through an appropriate representation of facial features from relevant face regions displayed in video streams and still images. A measure that is sensitive to facial movements is used in predefined regions of interest to detect the negative emotions. The experimentation has been performed on a standard dataset and live video streams and has showed promising results.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
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