Age Invariant Face Recognition Based on DCT Feature Extraction and Kernel Fisher Analysis


Leila Boussaad, Mohamed Benmohammed, Redha Benzid, Journal of Information Processing Systems
Vol. 12, No. 3, pp. 392-409, Jun. 2016
10.3745/JIPS.02.0043
Keywords: Active Appearance Model, Age-Invariant, Face recognition, Kernel Fisher Analysis, 2D-Discrete Cosine Transform
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Abstract

The aim of this paper is to examine the effectiveness of combining three popular tools used in pattern recognition, which are the Active Appearance Model (AAM), the two-dimensional discrete cosine transform (2D-DCT), and Kernel Fisher Analysis (KFA), for face recognition across age variations. For this purpose, we first used AAM to generate an AAM-based face representation; then, we applied 2D-DCT to get the descriptor of the image; and finally, we used a multiclass KFA for dimension reduction. Classification was made through a K-nearest neighbor classifier, based on Euclidean distance. Our experimental results on face images, which were obtained from the publicly available FG-NET face database, showed that the proposed descriptor worked satisfactorily for both face identification and verification across age progression.


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Cite this article
[APA Style]
Leila Boussaad, Mohamed Benmohammed, & Redha Benzid (2016). Age Invariant Face Recognition Based on DCT Feature Extraction and Kernel Fisher Analysis. Journal of Information Processing Systems, 12(3), 392-409. DOI: 10.3745/JIPS.02.0043.

[IEEE Style]
L. Boussaad, M. Benmohammed and R. Benzid, "Age Invariant Face Recognition Based on DCT Feature Extraction and Kernel Fisher Analysis," Journal of Information Processing Systems, vol. 12, no. 3, pp. 392-409, 2016. DOI: 10.3745/JIPS.02.0043.

[ACM Style]
Leila Boussaad, Mohamed Benmohammed, and Redha Benzid. 2016. Age Invariant Face Recognition Based on DCT Feature Extraction and Kernel Fisher Analysis. Journal of Information Processing Systems, 12, 3, (2016), 392-409. DOI: 10.3745/JIPS.02.0043.