An automatic facial expression recognition system evaluated by different classifiers

This work proposes an automatic human-face expression recognition system that classifies seven different facial expressions: happiness, anger, sadness, surprise, disgust, fear and neutral. The experimental results show that the proposed system achieves the best hit hate using a linear discriminant classifier, 99.71% and 99.55% for MUG and FEEDTUM databases respectively.