Multi-expression face recognition using neural networks and feature approximation

Authors:
Adnan Khashman;Akram A. Garad
Affiliations:
Electrical & Electronic Engineering Department, Near East University, Nicosia, Cyprus;Electrical & Electronic Engineering Department, Near East University, Nicosia, Cyprus
Venue:
ISMIS'06 Proceedings of the 16th international conference on Foundations of Intelligent Systems
Year:
2006

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Abstract

A human face is a complex object with features that can vary over time. Face recognition systems have been investigated while developing biometrics technologies. This paper presents a face recognition system that uses eyes, nose and mouth approximations for training a neural network to recognize faces in different expressions such as natural, smiley, sad and surprised. The developed system is implemented using our face database and the ORL face database. A comparison will be drawn between our method and two other face recognition methods; namely PCA and LDA. Experimental results suggest that our method performs well and provides a fast, efficient system for recognizing faces with different expressions.