Authors:
Rim Afdhal
;
Ridha Ejbali
and
Mourad Zaied
Affiliation:
Research Team on Intelligent Machines, National School of Engineers of Gabès, University of Gabès, Avenue Omar Ibn El Khattab, Zrig Eddakhlania 6029, Gabès, Tunisia
Keyword(s):
Emotion Recognition, Facial Expressions, Key Parts, Feature Points, Classification Rates.
Abstract:
Interaction between people is more than just verbal communication. According to scientific researches, human beings trust a lot on non-verbal techniques of communication, particularly communication and understanding each other via facial expressions. Facial expressions are more descriptive in situations where words fail, such as a surprise or a shock. In addition, lying via spoken words is harder to notice compared to faking expressions. Focusing on geometric positions of facial key parts and well detecting them is the best strategy to boost the classification rates of emotion recognition systems. The goal of this paper is to find the most relevant part of human face which is responsible to express a given emotion using feature points and to define a primary emotion by a minimum number of characteristic points. The proposed system contains four main parts: the face detection, the points location, the information extraction, and finally the classification.