PCA facial expression recognition

Inas H. El-Hori; Zahraa K. El-Momen; Ali Ganoun

doi:10.1117/12.2051196

24 December 2013 PCA facial expression recognition

Inas H. El-Hori, Zahraa K. El-Momen, Ali Ganoun

Proceedings Volume 9067, Sixth International Conference on Machine Vision (ICMV 2013); 906712 (2013) https://doi.org/10.1117/12.2051196
Event: Sixth International Conference on Machine Vision (ICMV 13), 2013, London, United Kingdom

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.

Citation Download Citation

Inas H. El-Hori, Zahraa K. El-Momen, and Ali Ganoun "PCA facial expression recognition", Proc. SPIE 9067, Sixth International Conference on Machine Vision (ICMV 2013), 906712 (24 December 2013); https://doi.org/10.1117/12.2051196

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