A Survey on Facial Expression Recognition using Machine Learning Techniques

In recent years, many researchers are taking an interest in the research area of Face recognition due to its diverse applications such as security systems, medical systems, entertainment. Nowadays, many kinds of biometric information processing systems are used for various purpose face-recognition systems. The facial expression that can define the human mental state and behavior and it is used for security purpose. FER is used in domains such as healthcare, marketing, environment, safety and social media. This paper presents the survey of the facial expression recognition system that includes the four main stages i.e. face detection, pre-processing, extraction of features, and classification. This research provides a broad overview of the FER process includes all stages of FER system as well as the various methods used to evaluate the efficiency of the various methods of facial expression recognition. This survey paper also helps to understand the approaches, different techniques that address and analyse the problems and challenges comes in the real-time environment. Finally, this paper concludes the state-of-the-art and explore the challenges faced in implementation of FER process along with the scope of future development.