AUTOMATIC FACIAL EXPRESSION RELATED EMOTION RECOGNITION USING MACHINE LEARNING TECHNIQUES

Facial expression are commonly used in everyday human communication for express the emotions. Emotions are reflected on the face, hand, body gesture and voice to express our feelings. In human communication, the facial expression is understanding of emotions help to achieve mutual sympathy. It is a nonverbal communications. Computer vision based technology is placed an important role in various applications especially in human emotion recognition process because emotions are related to the peoples mental ability and thinking process[1]. More ever, one single emotions leads to create the difficult health problems. Peoples affected by single emotions due to their stress, over thinking, personal problems and so on. So, their mental ability need to be maintained continoulsy for avoiding their health issues which is done by linking the emotion recognition system with computer vision area that effectively utilize the intelligent techniques [2]. The intelligent techniques analyze the human emotions from different parameters such as facial expression had electroencephalogram (EEG) brain activities with successful way. Among the parameters, facial expression based emotion recognition process is one of the easiest method because it does not require high cost, easy to capture the face expression [3] with the help of the digital camera, minimize the computation complexity also the impact of the facial expression is related with the brain activities and social impacts. There are there are 100 types of facial expressions such as blinking, cheerless, coy, blithe, deadpan, brooding, glowering, faint, grave, dejected, derisive, leering, moody, hopeless, slack-jawed and so on. These facial expressions are derived from the basic expressions such as Happy, Sad, Anger, Disgust, Surprise, Fear and Neutral