The belief theory for emotion recognition

0Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

Abstract

This paper presents a facial expression classification system based on a data fusion process using the theory of belief. Such expressions correspond to the six universal emotions (happiness, surprise, disgust, sadness, anger, and fear) as well as the neutral expression. The suggested algorithm rests on the decision fusion of both approaches: the global analysis and the local analysis of facial components. The classification result, throughout these two approaches, will be enhanced by fusion. The performance and the limitations of the recognition system and its ability to deal with different databases are identified through the analysis of a large number of results on the FEEDTUM database.

Cite

CITATION STYLE

APA

Mhamdi, H., Jarray, H., & Bouhlel, M. S. (2015). The belief theory for emotion recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9375 LNCS, pp. 517–526). Springer Verlag. https://doi.org/10.1007/978-3-319-24834-9_60

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free