Human emotion recognition with convolutional neural network

Abstract

The interaction between intelligent robots and humans has always been a hot issue, and researchers hope to make human-robot interaction as harmonious as human-human interaction. To achieve this, it is particularly important to enable robots to recognize human facial emotions automatically. However, many intelligent robots can already understand people's emotions through vocal communication. However, some people do not like to express their feelings through words, so it would be more convenient to let machines can automatically analyze people's facial emotions. This paper aims to make the machine recognize people's facial expressions and automatically analyze their emotions to make human-computer interaction more harmonious. The convolutional neural network has shown great influence on image feature extraction in the development of the machine learning field today. Therefore, this paper will adopt the advanced method of CNN to train the model on the FER2013 dataset. The abundant experiments demonstrate that the final trained model has good accuracy in recognizing three emotions: happy, surprise, and neutral.