Facial Expression Recognition Using Facial Movement Features

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Zhang, Ligang
Tjondronegoro, Dian
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2011
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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. 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.

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IEEE Transactions on Affective Computing

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2

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4

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© 2011 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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Information systems

Cognitive and computational psychology

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Computer Science, Artificial Intelligence

Computer Science, Cybernetics

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Zhang, L; Tjondronegoro, D, Facial Expression Recognition Using Facial Movement Features, IEEE Transactions on Affective Computing, 2011, 2 (4), pp. 219-229

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