Automatic Facial Feature Detection for ...
Document type :
Communication dans un congrès avec actes
Title :
Automatic Facial Feature Detection for Facial Expression Recognition
Author(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 Avancée - 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 Avancée - UAR 3380 [IRCICA]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
FOX MIIRE [LIFL]
Conference title :
Fifth International Conference on Computer Vision Theory and Applications (VISAPP) 2010
City :
Angers
Country :
France
Start date of the conference :
2010-05-17
Publication date :
2010
English keyword(s) :
Facial feature detection
emotion recognition
eye detection
mouth corner detection
emotion recognition
eye detection
mouth corner detection
HAL domain(s) :
Informatique [cs]/Traitement des images [eess.IV]
English abstract : [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 ...
Show more >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.Show less >
Show more >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.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
Source :
Files
- https://hal.archives-ouvertes.fr/hal-00812308/document
- Open access
- Access the document
- https://hal.archives-ouvertes.fr/hal-00812308/document
- Open access
- Access the document
- https://hal.archives-ouvertes.fr/hal-00812308/document
- Open access
- Access the document
- document
- Open access
- Access the document
- Automatic%20Facial%20Feature%20Detection%20for%20Facial%20Expression%20Recognition.pdf
- Open access
- Access the document