A comparative study on different approaches of real time human emotion recognition based on facial expression detection

Abstract

Facial Expression Recognition lies in one of the crucial areas of research for human-computer interaction and human emotion identification. For a system to recognize a facial expression it needs to come across multiple variability of human face like color, texture, posture, expression, orientation and so on. The first step to recognize a facial expression of a person with various facial movements of the muscles beneath the eyes, nose and lips are to be detected and further classifying those features by comparing them with a set of trained data values using a good classifier for recognizing the emotion. In this paper a comparative study of the different approaches initiated for automatic real-time facial expression recognition is undertaken along with their benefits and flaws which will further help in developing and improving the system.