Affect Recognition Using Magnitude Models ...
Document type :
Communication dans un congrès avec actes
Title :
Affect Recognition Using Magnitude Models of Motion
Author(s) :
Hadjerci, Oussama [Auteur]
FOX MIIRE [LIFL]
Lablack, Adel [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]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Institut de Recherche sur les Composants logiciels et matériels pour l'Information et la Communication Avancée - UAR 3380 [IRCICA]
FOX MIIRE [LIFL]
Lablack, Adel [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]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Institut de Recherche sur les Composants logiciels et matériels pour l'Information et la Communication Avancée - UAR 3380 [IRCICA]
Conference title :
MultiMedia Modelling 2014
City :
Dublin
Country :
Irlande
Start date of the conference :
2014-01-08
Journal title :
LNCS
Publication date :
2014-01-08
HAL domain(s) :
Informatique [cs]
Informatique [cs]/Intelligence artificielle [cs.AI]
Informatique [cs]/Intelligence artificielle [cs.AI]
English abstract : [en]
The analysis of human affective behavior has attracted increasing attention from researchers in psychology, computer science, neu-roscience, and related disciplines. We focus on the recognition of the affect state of a ...
Show more >The analysis of human affective behavior has attracted increasing attention from researchers in psychology, computer science, neu-roscience, and related disciplines. We focus on the recognition of the affect state of a single person from video streams. We create a model that allows to estimate the state of four affective dimensions of a person which are arousal, anticipation, power and valence. This sequence model is composed of a magnitude model of motion constructed from a set of point of interest tracked using optical flow. The state of the affective dimension is then predicted using SVM. The experimentation has been performed on a standard dataset and has showed promising results.Show less >
Show more >The analysis of human affective behavior has attracted increasing attention from researchers in psychology, computer science, neu-roscience, and related disciplines. We focus on the recognition of the affect state of a single person from video streams. We create a model that allows to estimate the state of four affective dimensions of a person which are arousal, anticipation, power and valence. This sequence model is composed of a magnitude model of motion constructed from a set of point of interest tracked using optical flow. The state of the affective dimension is then predicted using SVM. The experimentation has been performed on a standard dataset and has showed promising results.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
Source :