Deep Convolutional Neural Network for Robust Facial Emotion Recognition

Emotion and the ability to understand them are considered a channel of non-verbal communication. It is an important factor to achieve a smooth and yet robust interaction between machines and humans. In this paper, we review CNN-based methods for facial emotion recognition and we propose a new cutting edge deep learning approach to classify facial expressions from pictures. To guarantee the efficacy of the method, we used multiple datasets: FER2013, AffectNet, RaFD, and KDEF. We obtained results respectively 82.3%, 76.79%, 78.58 %, and 77.08 %. Those results surpassed the current state of the art. We also compared our achieved measurements to available APIs for facial emotion recognition.