Development of a person's facial expression recognition system using a convolutional neural network

Abstract

Humans naturally and intuitively use important and powerful facial expressions to communicate and show their emotions during social interactions. In that interaction, the effort to interpret someone's emotional condition is important in good communication. A person's emotional condition is reflected in the form of words, gestures, and especially facial expressions. Although humans can recognize expressions well, research on expression recognition carried out by machines is continuously being carried out in order to be able to carry out expression recognition in human and computer interactions. This research conducted facial expression recognition using the Convolutional Neural Network method. To perform facial expression recognition, the Convolutional Neural Network is trained with expression image data. The training process is carried out using different optimizer values, batch size, and epoch to get the best model. To overcome overfitting, data augmentation was carried out on training data and validation data. The experimental results in this research indicate that the system method built is able to recognize a person's facial expressions with an accuracy rate of 80%.