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Region-based facial expression recognition in still images


Citation

Nagi, Gawed M. and O. K. Rahmat, Rahmita Wirza and Khalid, Fatimah and Abdullah, Muhamad Taufik (2013) Region-based facial expression recognition in still images. Journal of Information Processing Systems, 9 (1). pp. 173-188. ISSN 1976-913X; ESSN: 2092-805X

Abstract

In Facial Expression Recognition Systems (FERS), only particular regions of the face are utilized for discrimination. The areas of the eyes, eyebrows, nose, and mouth are the most important features in any FERS. Applying facial features descriptors such as the local binary pattern (LBP) on such areas results in an effective and efficient FERS. In this paper, we propose an automatic facial expression recognition system. Unlike other systems, it detects and extracts the informative and discriminant regions of the face (i.e., eyes, nose, and mouth areas) using Haar-feature based cascade classifiers and these region-based features are stored into separate image files as a preprocessing step. Then, LBP is applied to these image files for facial texture representation and a feature-vector per subject is obtained by concatenating the resulting LBP histograms of the decomposed region-based features. The one-vs-rest SVM, which is a popular multi-classification method, is employed with the Radial Basis Function (RBF) for facial expression classification. Experimental results show that this approach yields good performance for both frontal and near-frontal facial images in terms of accuracy and time complexity. Cohn-Kanade and JAFFE, which are benchmark facial expression datasets, are used to evaluate this approach.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Computer Science and Information Technology
DOI Number: https://doi.org/10.3745/JIPS.2013.9.1.173
Publisher: Korea Information Processing Society
Keywords: Facial Expression Recognition (FER); Facial features detection; Facial features extraction; Cascade classifier; LBP; One-vs-rest SVM
Depositing User: Nida Hidayati Ghazali
Date Deposited: 03 Jun 2014 00:44
Last Modified: 25 Oct 2018 06:51
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.3745/JIPS.2013.9.1.173
URI: http://psasir.upm.edu.my/id/eprint/30644
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