Real-Time Detection and Classification of Facial Emotions

Abstract

Facial emotion detection and recognition is an emerging research field in detecting expression on a human’s face. Deep learning (DL) algorithms have gained immense success in various areas of implementation such as classification, recommendation models, object recognition, etc. Various types of modules that are brought together in this proposed technique for the betterment of the working are mainly contributed by the progressing field of deep learning mainly consisting of Convolutional Neural Networks (CNN) and Facial Emotion Recognition (FER). The FER is used to classify seven emotions on human faces. To develop higher efficiency, we also applied other essential techniques such as histogram equalization and background subtraction to the classification. Our proposed model provided 97 percent on average in seven-class recognition.