An E-Learning System with Multifacial Emotion Recognition Using Supervised Machine Learning
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Date
2016
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
E-Learning systems based on Affective computingare popularly used for emotional/behavioral analysis of the users. Emotions expressed by the user is depicted by detecting the facialexpression of the user and accordingly the teaching strategies willbe changed. The present eLearning systems mainly focus on thesingle user face detection. Hence, in this paper, we proposemultiuser face detection based eLearning system using supportvector machine based supervised machine learning technique. Experimental results demonstrate that the proposed systemprovides the accuracy of 89% to 100% w.r.t different datasets(LFW, FDDB, and YFD). Further, to improve the speed ofemotional feature processing, we used GPU along with the CPUand thereby achieve a speedup factor of 2. © 2015 IEEE.
Description
Keywords
Active Appearance Model, Affective Computing, eLearning, Facial expression recognition, Local Binary Patterns, Machine Learning
Citation
Proceedings - IEEE 7th International Conference on Technology for Education, T4E 2015, 2016, Vol., , p. 23-26
