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Comparison of principal component analysis and linear discriminant analysis for face recognition (March 2007)

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2 Author(s)
Robinson, P.E. ; Univ. of Johannesburg, Johannesburg ; Clarke, W.A.

In this paper two face recognition techniques, principal component analysis (PCA) and linear discriminant analysis (LDA), are considered and implemented using a nearest neighbor classifier. The performance of the two techniques is then compared in facial recognition and detection tasks. The comparisons are done using a facial recognition database captured for the project that contains images captured over a range of poses, lighting conditions and occlusions.

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Date of Conference:

26-28 Sept. 2007