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, detected faces are processed to perform the
characterization phase through computed vectors of Zernike
moments. At last step, a back propagation neural network was
trained to distinguish between the seven emotion’s states of a
presented face. Finally, method performances were evaluated
on the well known JAFEE and YALE database.

Information

Item Type:	Conference
Divisions:	» Laboratory of Electrical Engineering and Renewable Energy » Faculty of Science and Technology
ePrint ID:	99
Date Deposited:	2014-10-30
Further Information:	Google Scholar
URI:	https://www.univ-soukahras.dz/en/publication/article/99

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