Automatic Facial Feature Detection for ...
Type de document :
Communication dans un congrès avec actes
Titre :
Automatic Facial Feature Detection for Facial Expression Recognition
Auteur(s) :
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]
Ihaddadene, Nacim [Auteur]
FOX MIIRE [LIFL]
no affiliation
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 Avancé - UAR 3380 [IRCICA]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
FOX MIIRE [LIFL]
FOX MIIRE [LIFL]
Bilasco, Ioan Marius [Auteur]
Université de Lille, Sciences et Technologies
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
FOX MIIRE [LIFL]
Ihaddadene, Nacim [Auteur]
FOX MIIRE [LIFL]
no affiliation
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 Avancé - UAR 3380 [IRCICA]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
FOX MIIRE [LIFL]
Titre de la manifestation scientifique :
Fifth International Conference on Computer Vision Theory and Applications (VISAPP) 2010
Ville :
Angers
Pays :
France
Date de début de la manifestation scientifique :
2010-05-17
Date de publication :
2010
Mot(s)-clé(s) en anglais :
Facial feature detection
emotion recognition
eye detection
mouth corner detection
emotion recognition
eye detection
mouth corner detection
Discipline(s) HAL :
Informatique [cs]/Traitement des images [eess.IV]
Résumé en anglais : [en]
This paper presents a real-time automatic facial feature point detection method for facial expression recognition. The system is capable of detecting seven facial feature points (eyebrows, pupils, nose, and corners of ...
Lire la suite >This paper presents a real-time automatic facial feature point detection method for facial expression recognition. The system is capable of detecting seven facial feature points (eyebrows, pupils, nose, and corners of mouth) in grayscale images extracted from a given video. Extracted feature points then used for facial expression recognition. Neutral, happiness and surprise emotions have been studied on the Bosphorus dataset and tested on FG-NET video dataset using OpenCV. We compared our results with previous studies on this dataset. Our experiments showed that proposed method has the advantage of locating facial feature points automatically and accurately in real-time.Lire moins >
Lire la suite >This paper presents a real-time automatic facial feature point detection method for facial expression recognition. The system is capable of detecting seven facial feature points (eyebrows, pupils, nose, and corners of mouth) in grayscale images extracted from a given video. Extracted feature points then used for facial expression recognition. Neutral, happiness and surprise emotions have been studied on the Bosphorus dataset and tested on FG-NET video dataset using OpenCV. We compared our results with previous studies on this dataset. Our experiments showed that proposed method has the advantage of locating facial feature points automatically and accurately in real-time.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :
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