Facial expression recognition using facial movement features

Zhang, Ligang & Tjondronegoro, Dian W. (2011) Facial expression recognition using facial movement features. IEEE Transactions on Affective Computing.

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Abstract

Facial expression is an important channel for human communication and can be applied in many real applications. One critical step for facial expression recognition (FER) is to accurately extract emotional features. Current approaches on FER in static images have not fully considered and utilized the features of facial element and muscle movements, which represent static and dynamic, as well as geometric and appearance characteristics of facial expressions. This paper proposes an approach to solve this limitation using ‘salient’ distance features, which are obtained by extracting patch-based 3D Gabor features, selecting the ‘salient’ patches, and performing patch matching operations. The experimental results demonstrate high correct recognition rate (CRR), significant performance improvements due to the consideration of facial element and muscle movements, promising results under face registration errors, and fast processing time. The comparison with the state-of-the-art performance confirms that the proposed approach achieves the highest CRR on the JAFFE database and is among the top performers on the Cohn-Kanade (CK) database.

Impact and interest:

50 citations in Scopus
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35 citations in Web of Science®

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ID Code: 43787
Item Type: Journal Article
Refereed: Yes
Additional Information: IEEE First Online Publication
Keywords: facial expression analysis, feature evaluation and selection, computer vision, Gabor filter, Adaboost
DOI: 10.1109/T-AFFC.2011.13
ISSN: 1949-3045
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2011 IEEE
Copyright Statement: Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Deposited On: 04 Aug 2011 03:37
Last Modified: 06 Aug 2011 03:23

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