Title: New face expression recognition using polar angular radial transform and principal component analysis

Authors: Imène Taleb; Madani Ould Mammar; Abdelaziz Ouamri

Addresses: Department of Electronics, Faculty of Electrical Engineering, Université des sciences et de la technologie d'Oran – Mohamed-Boudiaf, B.P. 1505. El Mnaouer, Oran, 31000, Algeria ' Department of Electronics, Faculty of Electrical Engineering, Université des sciences et de la technologie d'Oran – Mohamed-Boudiaf, B.P. 1505. El Mnaouer, Oran, 31000, Algeria ' Department of Electronics, Faculty of Electrical Engineering, Université des sciences et de la technologie d'Oran – Mohamed-Boudiaf, B.P. 1505. El Mnaouer, Oran, 31000, Algeria

Abstract: This paper presents a new method for facial expression recognition (FER) using a polar mathematical development based on the angular radial transformation (ART). This method is combined by polar angular radial transform (P-ART) and principal component analysis (PCA). The new ART is a powerful descriptor in terms of robustness, description form and way more information-rich compared to the conventional Cartesian descriptor. Support vector machine (SVM) training is used to recognise the facial expression for an input face image. Finally, the experimental results show the performance of the P-ART and the PCA. The fusion of these two techniques can be better than other existing methods of recognition of facial expression. During the experiment, the basis of facial given Japanese female facial expression (JAFFE) and the Cohn-Kanade databases has been used.

Keywords: facial expression recognition; FER; polar angular radial transform; P-ART; principal component analysis; PCA; support vector machine; SVM; fusion; Japanese female expression; JAFFE; Cohn-Kanade.

DOI: 10.1504/IJBM.2018.091633

International Journal of Biometrics, 2018 Vol.10 No.2, pp.176 - 194

Received: 12 Dec 2017
Accepted: 05 Feb 2018
Published online: 08 May 2018 *

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