Facial Expression Recognition Using Neural Network

Abstract

Human emotions are states of mental health that resolve spontaneously rather than through conscious exertion, and are accompanied by physiological changes in the facial muscles that signify expressions. Nonverbal communication methods such as expressions, eye movements, and gestures are used in many applications of human-computer interaction. Identifying emotions is not an easy task because there is no difference between the emotions of a face, and there is also a lot of complexity and variability. The machine learning algorithm uses some open features to model the face. In this work, convolutional neural networks (CNNs) were developed to identify the expression of facial emotions. Facial expressions play an important role in the nonverbal communication that takes place in a person’s inner emotions that are reflected on his or her face.This work has been used the Viola-Jones algorithm to detect the eye and lips region from a face and then with the help of the neural network. Also, Machine Learning techniques, Deep Learning models, and Neural Network algorithms are used for emotion recognition. This work will be proposed as an effective way to detect anger, contempt, disgust, fear, happiness, sadness, and surprise.