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Classifying student’s faces for teaching assistant system

Suraini, Nur Surayahani and Ahmad, Ida Laila and Mohamed, Masnani and Lee, B.S. (2010) Classifying student’s faces for teaching assistant system. In: Recent Advances and Applications of Electrical Engineering. WSEAS Press, pp. 216-220. ISBN 9789604741717

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Abstract

This paper describes the facial emotion recognition to determine the student’s conditions. The facial emotion recognition could be envisioned to sense the student’s attention state through a CCD camera. Therefore, facial images were analyzed to extract the features to characterize the variations between two categories of student’s faces (understand or unsure/confused) images. The features extraction techniques applywas Principal Component Analysis (PCA), this algorithm finds the principle components of the covariance matrix of a set of face images. Then, the eigenvalues component will be used as an input to the Minimum Distance classifier. The ultimate goal of this research is to develop an intelligent system to investigate the relation between teaching quality contents and comprehension in learning according to the specific emotion state.

Item Type: Book Section
Uncontrolled Keywords: face recognition, Principal Component Analysis (PCA)
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Divisions: Faculty of Electrical and Electronic Engineering > Department of Computer Engineering
Depositing User: Nurul Elmy Mohd. Yusof
Date Deposited: 14 Apr 2010 07:43
Last Modified: 29 Apr 2011 06:40
URI: http://eprints.uthm.edu.my/id/eprint/357
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