Title
Belief theory applied to facial expressions classification
Abstract
A novel and efficient approach to facial expression classification based on the belief theory and data fusion is presented and discussed. The considered expressions correspond to three (joy, surprise, disgust) of the six universal emotions as well as the neutral expression. A robust contour segmentation technique is used to generate an expression skeleton with facial permanent features (mouth, eyes and eyebrows). This skeleton is used to determine the facial features deformations occurring when an expression is present on the face defining a set of characteristic distances. In order to be able to recognize “pure” as well as “mixtures” of facial expressions, a belief-theory based fusion process is proposed. The performances and the limits of the proposed recognition method are highlighted thanks to the analysis of a great number of results on three different test databases: the Hammal-Caplier database, the Cohn-Kanade database and the Cottrel database. Preliminary results demonstrate the interest of the proposed approach, as well as its ability to recognize non separable facial expressions.
Year
DOI
Venue
2005
10.1007/11552499_21
ICAPR (2)
Keywords
Field
DocType
belief theory,facial permanent feature,facial expressions classification,hammal-caplier database,expression skeleton,cohn-kanade database,neutral expression,cottrel database,facial expression,facial feature,facial expression classification,non separable facial expression,data fusion
Belief theory,Computer vision,Expression (mathematics),Pattern recognition,Computer science,Segmentation,Sensor fusion,Eyebrow,Facial expression,Artificial intelligence,Surprise
Conference
Volume
ISSN
ISBN
3687
0302-9743
3-540-28833-3
Citations 
PageRank 
References 
6
0.55
5
Authors
3
Name
Order
Citations
PageRank
Z. Hammal1765.06
A. Caplier215411.64
M. Rombaut3766.90