Recognition of Facial Expressions Using Vision Transformer

Abstract

The identification of emotions through the reading of non-verbal signals, such as gestures and facial expressions, has generated a new application in the field of Facial Expression Recognition (FER) and human-computer interaction. Through the recognition of facial expressions, it would be possible to improve industrial equipment by making it safer through social intelligence that has excellent applications in the area of industrial security. That is why this research proposes to classify a series of images from the database called FER-2013, which contains data on seven different emotions, which are anger, disgust, fear, joy, sadness, surprise, neutral. For the recognition of expressions, a Vision Transformer architecture was implemented, of which 87% precision was obtained, while the top test accuracy was 99%.