Feature Extraction Techniques for Facial Expression Recognition Systems

Automatic facial expression recognition has become a progressive research area since it plays a major role in human computer interaction. The facial expression recognition finds its major application in areas like social interaction and social intelligence. However it is not an easy task because the facial image, facial occlusion, face color/shape etc. is not easy to deal with. In this paper, various techniques for feature extraction like Gabor filters, Principal Component Analysis (PCA), Local Binary Patterns (LBP), Linear Discriminant Analysis (LDA), DCT , with different classifiers like Support Vector Machine(SVM) and Neural Networks, which are used to recognize human expression in various conditions on different databases are being examined. Citation:Nifi C Joy, Federal Iinstitute of Science and Technology, Mookkannoor P O, Angamaly, Ernakulam, Kerala 683577;Prasad J.C. ,Federal Institute of Science and Technology. "Feature Extraction Techniques for Facial Expression Recognition Systems." Global Research and Development Journal For Engineering 12 2016: 22 - 25.