NDLI: Facial expression recognition using high order directional derivative local binary patterns

Content Provider	IEEE Xplore Digital Library
Author	Tabatabaei, S.M. Chalechale, A. Moghimi, S.
Copyright Year	2015
Description	Author affiliation: Dept. of Comput. Eng., Islamic Azad Univ. of Najafabad, Najafabad, Iran (Moghimi, S.) \|\| Dept. of Comput. Eng., Razi Univ., Kermanshah, Iran (Tabatabaei, S.M.; Chalechale, A.)
Abstract	The most expressive manner which human can reveal his emotional states is facial expression. Automatic facial expression recognition is an emerging field of study having extensive applications among which the human-computer interaction (HCI) has received lots of attentions in recent years. The features extracted from facial images, in order to recognize facial expressions, play an essential role in effectiveness of the facial image descriptors. Local binary pattern (LBP) texture descriptors have been known as simple, yet efficient descriptors which are noticeably used for extracting facial patterns from images. Recently, a generalized form of local binary pattern has been introduced which can offer a more precise image description than simple LBP descriptors. Consequently, it would be expected that taking the advantage of using these new LBP texture descriptors will produce more promising results in comparison with use of simple local binary pattern descriptors. In this paper, a novel method has been proposed for image feature extraction using these new image texture descriptors (generalized LBP); then, the obtained results have been compared to the results produced when applying simple LBP descriptors. Furthermore, K-NN and SVM have been used as classifiers in the proposed approach. Finally, a comparison between the proposed method and the existing local binary pattern algorithms for facial expression recognition concludes the superiority of the proposed algorithm over its existing counterparts.
Starting Page	1
Ending Page	5
File Size	801467
Page Count	5
File Format	PDF
e-ISBN	9781479984459
DOI	10.1109/PRIA.2015.7161619
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-03-11
Publisher Place	Iran
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Histograms Facial expression recognition Image recognition Image analysis Face recognition Derivative local binary patterns Feature extraction Support vector machine
Content Type	Text
Resource Type	Article

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