In this paper, we introduce a new facial-expression analysis system designed to automatically recognize facial expressions, able to manage facial-expression intensity variation as well as reducing the doubt and confusion between facial-expression classes. Our proposed approach introduces a new method to segment efficiently facial feature contours using Vector Field Convolution (VFC) technique. Relying on the detected con- tours, we extract facial feature points which go with facial-expression deformations. Then we have modeled a set of distances among the detected points to define prediction rules through data mining technique. An experimental study was conducted to evaluate the per- formance of our proposed solution under varying factors.
['Hazar Mliki', 'Nesrine Fourati', 'Mohamed Hammami', 'Hanêne Ben-Abdallah']
Data Mining-based Facial Expressions Recognition System