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Modeling understanding level based student face classification

Suriani , Nor Surayahani and Mohamed, Masnani (2010) Modeling understanding level based student face classification. In: Fourth Asia International Conference on Mathematical/Analytical Modelling and Computer Simulation (AMS 2010 ), 26-28 May 2010, Kota Kinabalu, Malaysia.

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This paper describes the student’s facial emotion recognition to determine their current state of mind. The facial emotion recognition of the student could be envisioned to sense their attention states through a video camera. Therefore, facial images were analyzed to extract the features using Principal Component Analysis (PCA) algorithm. Then, the eigenvalues component were used as an input to the Minimum Distance Classifier which characterized between two categories of students (understand or unsure/confused). These emotions were promising to be significant in modeling the attention states which will be useful in detecting abnormal attention or focus during the teaching and learning session. The ultimate goal of this research is to develop a teaching monitoring system by modeling the understanding and attention level. Therefore, the low attention level model will alarm a warning signal which indicates the current situation of teaching delivery, quality contents and learning comprehension.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: principal component analysis (PCA); facial emotions classification
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Divisions: Faculty of Electrical and Electronic Engineering > Department of Computer Engineering
Depositing User: Normajihan Abd. Rahman
Date Deposited: 22 Feb 2013 03:59
Last Modified: 21 Jan 2015 07:28
URI: http://eprints.uthm.edu.my/id/eprint/3061
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