An E-Learning System with Multifacial Emotion Recognition Using Supervised Machine Learning

dc.contributor.authorAshwin, T.S.
dc.contributor.authorJose, J.
dc.contributor.authorRaghu, G.
dc.contributor.authorGuddeti, G.R.
dc.date.accessioned2026-02-06T06:39:13Z
dc.date.issued2016
dc.description.abstractE-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.
dc.identifier.citationProceedings - IEEE 7th International Conference on Technology for Education, T4E 2015, 2016, Vol., , p. 23-26
dc.identifier.urihttps://doi.org/10.1109/T4E.2015.21
dc.identifier.urihttps://idr.nitk.ac.in/handle/123456789/32170
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.subjectActive Appearance Model
dc.subjectAffective Computing
dc.subjecteLearning
dc.subjectFacial expression recognition
dc.subjectLocal Binary Patterns
dc.subjectMachine Learning
dc.titleAn E-Learning System with Multifacial Emotion Recognition Using Supervised Machine Learning

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