Title :

Intelligent pixels of interest selection with application to facial expression recognition using multilayer perceptron

Author(s) :

Danisman, Taner [Auteur]
FOX MIIRE [LIFL]
Bilasco, Ioan Marius [Auteur]
FOX MIIRE [LIFL]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Université de Lille, Sciences et Technologies
Martinet, Jean [Auteur]
FOX MIIRE [LIFL]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Djeraba, Chaabane [Auteur]
no affiliation
FOX MIIRE [LIFL]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]

Journal title :

Signal Processing
Special issue on Machine Learning in Intelligent Image Processing

Pages :

1547-1556

Publisher :

Elsevier

Publication date :

2013

ISSN :

0165-1684

English keyword(s) :

Facial expression recognition
multi layer perceptron
feature selection * Corresponding author

HAL domain(s) :

Informatique [cs]
Informatique [cs]/Intelligence artificielle [cs.AI]
Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]

English abstract : [en]

This paper presents an automatic way to discover pixels in a face image that improves the facial expression recognition results. Main contribution of our study is to provide a practical method to improve classification ...
Show more >This paper presents an automatic way to discover pixels in a face image that improves the facial expression recognition results. Main contribution of our study is to provide a practical method to improve classification performance of classifiers by selecting best pixels of interest. Our method exhaustively searches for the best and worst feature window position from a set of face images among all possible combinations using MLP. Then, it creates a non-rectangular emotion mask for feature selection in supervised facial expression recognition problem. It eliminates irrelevant data and improves the classification performance using backward feature elimination. Experimental studies on GENKI, JAFFE and FERET databases showed that the proposed system improves the classification results by selecting the best pixels of interest.Show less >

Language :

Anglais

Popular science :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL