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Proceedings Paper

PCA facial expression recognition
Author(s): Inas H. El-Hori; Zahraa K. El-Momen; Ali Ganoun
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Paper Abstract

This paper explores and compares techniques for automatically recognizing facial actions in sequences of images. The comparative study of Facial Expression Recognition (FER) techniques namely Principal Component’s analysis (PCA) and PCA with Gabor filters (GF) is done. The objective of this research is to show that PCA with Gabor filters is superior to the first technique in terms of recognition rate. To test and evaluates their performance, experiments are performed using real database by both techniques. The universally accepted five principal emotions to be recognized are: Happy, Sad, Disgust and Angry along with Neutral. The recognition rates are obtained on all the facial expressions.

Paper Details

Date Published: 24 December 2013
PDF: 5 pages
Proc. SPIE 9067, Sixth International Conference on Machine Vision (ICMV 2013), 906712 (24 December 2013); doi: 10.1117/12.2051196
Show Author Affiliations
Inas H. El-Hori, Univ. of Tripoli (Libyan Arab Jamahiriya)
Zahraa K. El-Momen, Univ. of Tripoli (Libyan Arab Jamahiriya)
Ali Ganoun, Univ. of Tripoli (Libyan Arab Jamahiriya)


Published in SPIE Proceedings Vol. 9067:
Sixth International Conference on Machine Vision (ICMV 2013)
Branislav Vuksanovic; Antanas Verikas; Jianhong Zhou, Editor(s)

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