Abstract

Neural network classifying method is used in this work to perform facial expression recognition. The processed expressions were the six most pertinent facial expressions and the neutral one. This operation was implemented in three steps. First, a neural network, trained using Zernike moments, was applied to the set of the well known Yale and JAFFE database images to perform face detection. In the second step, Auto Regressive modeling (AR) using 2D-Burg filter was used for facial parameterization. At the last step, a neural network, trained on a set of the AR models, was applied to the rest of the images models to test method\'s performances

Information

Item Type:	Conference
Divisions:	» Faculty of Science and Technology
ePrint ID:	34
Date Deposited:	2014-10-30
Further Information:	Google Scholar
URI:	https://www.univ-soukahras.dz/en/publication/article/34

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