<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Boussaad, Leila</style></author><author><style face="normal" font="default" size="100%">Benmohammed, Mohamed</style></author><author><style face="normal" font="default" size="100%">Benzid, Redha</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Age Invariant Face Recognition Based on DCT Feature Extraction and Kernel Fisher Analysis</style></title><secondary-title><style face="normal" font="default" size="100%">Journal of Information Processing SystemsJournal of Information Processing Systems</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016</style></date></pub-dates></dates><number><style face="normal" font="default" size="100%">3</style></number><volume><style face="normal" font="default" size="100%">12</style></volume><pages><style face="normal" font="default" size="100%">392-409</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">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.</style></abstract></record></records></xml>