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DOI: 10.14569/IJACSA.2013.040314
PDF

Robust Facial Expression Recognition via Sparse Representation and Multiple Gabor filters

Author 1: Rania Salah El-Sayed
Author 2: Prof.Dr. Ahmed El Kholy
Author 3: Prof.Dr. Mohamed Youssri El-Nahas

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 4 Issue 3, 2013.

  • Abstract and Keywords
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Abstract: Facial expressions recognition plays important role in human communication. It has become one of the most challenging tasks in the pattern recognition field. It has many applications such as: human computer interaction, video surveillance, forensic applications, criminal investigations, and in many other fields. In this paper we propose a method for facial expression recognition (FER). This method provides new insights into two issues in FER: feature extraction and robustness. For feature extraction we are using sparse representation approach after applying multiple Gabor filter and then using support vector machine (SVM) as classifier. We conduct extensive experiments on standard facial expressions database to verify the performance of proposed method. And we compare the result with other approach.

Keywords: Facial expression recognition (FER); L1-minimization; sparse representation; Gabor filters; support vector machine (SVM).

Rania Salah El-Sayed, Prof.Dr. Ahmed El Kholy and Prof.Dr. Mohamed Youssri El-Nahas, “Robust Facial Expression Recognition via Sparse Representation and Multiple Gabor filters” International Journal of Advanced Computer Science and Applications(IJACSA), 4(3), 2013. http://dx.doi.org/10.14569/IJACSA.2013.040314

@article{El-Sayed2013,
title = {Robust Facial Expression Recognition via Sparse Representation and Multiple Gabor filters},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2013.040314},
url = {http://dx.doi.org/10.14569/IJACSA.2013.040314},
year = {2013},
publisher = {The Science and Information Organization},
volume = {4},
number = {3},
author = {Rania Salah El-Sayed and Prof.Dr. Ahmed El Kholy and Prof.Dr. Mohamed Youssri El-Nahas}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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