RESULT ANALYSIS OF FACIAL EXPRESSION RECOGNITION TECHNIQUES

Expression recognition possesses practically significant importance; it offers vast application prospects, such as user - friendly interface between people and machine, humanistic design of products, and an automatic robot for example. Face perception is an important component of human knowledge. Faces contain much information about ones ’ i d and also about mood and state of mind. Facial expression interactions usually relevant in social life, teacher - student interaction, credibility in numerous contexts, medicine etc. however people can easily recognize facial expression easily, but it is qu ite hard for a machine to do this. The comparative study of Facial Expression Recognition techniques namely Principal Component analysis (PCA), PCA with neural networks(NN) is done .The objective of this research is to show that PCA with NN is superior to former technique in term s of recognition rate .To test and evaluate their performance, experiments are performed using JAFEE and real database using both techniques. The universally accepted seven principal emotions to be recognized are: Angry, Happy, Sad, Disgust, fear, Surprise and neutral.