Automatic Facial Expression Recognition System Based on Geometric and Appearance Features

This paper presents a computer vision system for automatic facial expression recognition (AFER). The robust AFER system can be applied in many areas such as emotion science, clinical psychology and pain assessment it includes facial feature extraction and pattern recognition phases that discriminates among different facial expressions. In feature extraction phase a combination between holistic and analytic approaches is presented to extract 83 facial expression features. Expression recognition is performed by using radial basis function based artificial neural network to recognize the six basic emotions (anger, fear, disgust, joy, surprise, sadness). The experimental results show that 96% recognition rate can be achieved when applying the proposed system on person-dependent database and 93.5% when applying on person-independent one.