A REVIEW ON AUTOMATIC FACIAL EXPRESSION RECOGNITION SYSTEMS

The automatic facial expression recognition (FER) system is an important concept in human computer interface (HCI), as human face is a part that gives information about the state of user’s behavior through various expressions. This study of recognizing facial expression is one of the challenging research areas i n image analysis and computer vision. Since last 2 decades many researchers are working to make HCI machines to operate with more reliability and efficiency even in the worst conditions. In this paper, we studied different FER methods such as face detecti on, feature extraction and expression classification where techniques like Knowledge - based, Feature - based, Principal Component Analysis (PCA), Independent Component Analysis (ICA), Gabor filters, Local Binary Patterns (LBP) with a range of classifiers like a SVM, Adaboost, HMM etc are been compared.