Automatic Human Emotion Recognition System using Facial Expressions with Convolution Neural Network

Emotion recognition using facial expression is very much necessary these days. Different kinds of emotions reflect a different definitions. Facial emotion recognition plays a major role in driver warning systems, it can also play an important role in shopping malls to predict unusual activity like terrorist attacks, robbery and much more. Predicting the suicidal tendency of a person also can be done using facial emotion recognition. An automatic facial emotion classification system is proposed in this paper using the Convolution Neural Network (CNN) with the features extracted from the Speeded Up Robust Features (SURF). 91% accuracy is achieved with the proposed model which supports tracking human emotion with facial expressions.