Facial Emotions Recognition using Convolutional Neural Network

This book summarizes Facial expression recognition and identifies emotion from a face image, it is a manifestation of the activity and personality of a human. In the 20th century, the American psychologist Ekman and Friesen defined six basic emotions (anger, fear, disgust, sadness, surprise, and happiness), which are the same across cultures. Facial expression recognition has brought much attention in the past years due to its impact on clinical practice, social robotics, and education. According to diverse research, emotion plays an important role in education. we presented a Convolutional Neural Network model for students¿ facial expression recognition. The proposed model includes 4 convolutional layers, 4 max-pooling, and 2 fully connected layers. The system recognizes faces from students' input images using a Haar-like detector and classifies them into seven facial expressions: surprise, fear, disgust, sad, happy, anger, and neutral.