Improving the performance of facial expression recognition using dynamic, subtle and regional features

Zhang, Ligang & Tjondronegoro, Dian W. (2010) Improving the performance of facial expression recognition using dynamic, subtle and regional features. Neural Information Processing. Models and Applications, pp. 582-589.

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Human facial expression is a complex process characterized of dynamic, subtle and regional emotional features. State-of-the-art approaches on facial expression recognition (FER) have not fully utilized this kind of features to improve the recognition performance. This paper proposes an approach to overcome this limitation using patch-based ‘salient’ Gabor features. A set of 3D patches are extracted to represent the subtle and regional features, and then inputted into patch matching operations for capturing the dynamic features. Experimental results show a significant performance improvement of the proposed approach due to the use of the dynamic features. Performance comparison with pervious work also confirms that the proposed approach achieves the highest CRR reported to date on the JAFFE database and a top-level performance on the Cohn-Kanade (CK) database.

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ID Code: 43788
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: Facial expression recognition, Adaboost, support vector machine
DOI: 10.1007/978-3-642-17534-3_72
ISSN: 0302-9743
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2010 Springer-Verlag
Copyright Statement: Conference proceedings published, by Springer Verlag, will be available via Lecture Notes in Computer Science
Deposited On: 04 Aug 2011 00:26
Last Modified: 22 Jul 2014 05:18

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