Emotion Recognition Using Convolutional Neural Network (CNN)

Abstract

Emotion is an expression that human use in expressing their feelings. It can be express through facial expression, body language and voice tone. Humans’ facial expression is a major way in conveying emotion since it is the most powerful, natural and universal signal to express humans’ emotion condition. However, humans’ facial expression has similar patterns, and it is very confusing in recognizing the expression using naked eye. For instance, afraid and surprised is very similar to one another. Thus, this will lead to confusion in determining the facial expression. Hence, this study aims to develop a mobile based application for emotion recognition that can recognize emotion based on facial expression in real-time. The Deep Learning based technique, Convolutional Neural Network (CNN) is implemented in this study. The MobileNet algorithm is deployed to train the model for recognition. There are four types of facial expressions to be recognized which are happy, sad, surprise, and disgusting. As the result, this study obtained 85% recognition accuracy. In the future, the developed application could be improved by adding more face expression categories.