Abstract: Predicting the student’s emotional engagements using Computer vision techniques are a challenging task. There are several works on computer vision based affective state recognition of students in the e-learning environment, there are limited works on affective state recognition of students in the classroom environment where more than one Student are present in a single image frame. Face recognition has become an attractive field in computer-based application development in the last few decades. The learning process has also evolved a lot. However, the emotion of students is usually neglected in the learning process. This project is mainly concerned about using facial expression to detect emotion in the learning environment. There are many algorithms for facial recognition and emotion capturing out of which we have used Convolutional neural network (CNN).The captured facial expression will be used in the Learning Environment for analyzing the learner mood. The proposed architecture uses the students’ facial expressions for analyzing their affective states. The experimental results will predict the probability of affective states of the faces detected in learning environment for understanding of emotions during learning process in order to enhance the learning and feedback achieving process.
Keywords: Face Detection, Face emotion recognition, Convolution neural network, OpenCV, Machine learning.
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DOI:
10.17148/IJARCCE.2021.106107
