Classifying student's faces for teaching assistant system

Suriani , Nor Surayahani and Lee, B.S. and Ahmad, Ida Laila and Mohamed, Masnani (2010) Classifying student's faces for teaching assistant system. In: AEE'10 Proceedings of the 9th WSEAS International Conference on Applications of Electrical Engineering.

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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 apply was 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:Conference or Workshop Item (Paper)
Uncontrolled Keywords:face recognition; principal component analysis (PCA)
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
ID Code:3569
Deposited By:Normajihan Abd. Rahman
Deposited On:11 Apr 2013 10:57
Last Modified:11 Apr 2013 10:57

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