Feature Extraction Techniques in Facial Expression Recognition

Abstract

Facial expression recognition became a very important and very challenging aera within past few years in computer science vision field. It (FER) a very hot and active topic for research. FER play interesting role in aera of computer vision processing. This paper reviews the different algorithms which is used in facial expression recognition. usually, Facial expression recognition has 3 Majour stages first one is preprocessing I.e., face detection second is Feature extraction or selection (the aim of this paper) and last one is classification. In this paper study we review some current work done for Facial expression recognition technique. we know that feature extraction method is very important step for image recognition so in this paper we see that after the preprocessing the images how feature extraction done, we see some technique like local binary pattern (LBP), Gabor filter etc. And also, this paper gives an evaluation of Majour characteristic feature extraction and based on that their performance in terms of accuracy and them limitations. arrangement of this FER paper is following in order: section I contain the introduction section II contains a sample process of facial expression recognition section III contains the different technique of feature extraction and section IV contains the review discussion and last section V contain the conclusion.to making these algorithms efficient and more effective feature extraction technique played an important role.