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Analysing Meticulous Behavior of Learners from Non-Verbal Cues

Mageshwaran L.*, Keerthivasan S. E. **, Hariharan K.***, Rajasekaran T.****

*-**** Department of Computer Science and Engineering, SRM Valliammai Engineering College, Kattankulathur, Tamil Nadu, India.

Periodicity:July - December'2020
DOI : https://doi.org/10.26634/jpr.7.2.18129

Abstract

Face emotion recognition is the most important part in deep learning. It is the best way to communicate in a non-verbal manner. The main issue, which has existed since the time, is that teachers are unable to determine whether or not their students have grasped the subject in class. The proposed model in this paper will address this issue. Face emotion recognition is becoming more popular with Artificial Intelligence. In our model, Convolutional Neural Networks is used for the emotion recognition. This is divided into two parts; face detection and extraction can be done using Haar cascades and the emotion will be extracted from the face using CNN on FER 2013. Then the emotion is collected continuously and the average will be stored in MySQL database. A user interface will be created to teachers and admin so that they can view the data of students at any time and also generate report on it. This proposed model will give the accuracy of 90%.

Keywords

Emotion Recognition Deep Learning, Convolutional Neural Networks, Haar Cascades, Face Action Coding System (FACS).

How to Cite this Article?

Mageshwaran, L., Keerthivasan, S. E., Hariharan, K. and Rajasekaran, T. (2020). Analysing Meticulous Behavior of Learners from Non-Verbal Cues. i-manager's Journal on Pattern Recognition, 7(2), 7-13. https://doi.org/10.26634/jpr.7.2.18129

References

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