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

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.