Authentication is a significant issue in system control in computer based communication. Human face recognition is an important branch of biometric verification and has been widely used in many applications, such as video monitor system, human-computer interaction, and door control system and network security. This paper describes a method for Student's Attendance System which will integrate with the face recognition technology using Personal Component Analysis (PCA) algorithm. The system will record the attendance of the students in class room environment automatically and it will provide the facilities to the faculty to access the information of the students easily by maintaining a log for clock-in and clock-out time.
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.
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