An E-learning System With Multifacial Emotion Recognition Using Supervised Machine Learning

E-Learning systems based on Affective computing are popularly used for emotional/behavioral analysis of the users. Emotions expressed by the user is depicted by detecting the facial expression of the user and accordingly the teaching strategies will be changed. The present eLearning systems mainly focus on the single user face detection. Hence, in this paper, we propose multiuser face detection based eLearning system using support vector machine based supervised machine learning technique. Experimental results demonstrate that the proposed system provides the accuracy of 89% to 100% w.r.t different datasets (LFW, FDDB, and YFD). Further, to improve the speed of emotional feature processing, we used GPU along with the CPU and thereby achieve a speedup factor of 2.