Facial Expression Recognition on Hexagonal Structure Using LBP-Based Histogram Variances

Wang, L; He, X; Du, R; Jia, W; Wu, Q; Yeh, W

Facial Expression Recognition on Hexagonal Structure Using LBP-Based Histogram Variances

Wang, L He, X Du, R Jia, W Wu, Q Yeh, W

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Publisher:: Springer Berlin Heildelberg New York
Publication Type:: Conference
Citation:: Wang Lin et al. 2011, 'Facial Expression Recognition on Hexagonal Structure Using LBP-Based Histogram Variances', , Springer Berlin Heildelberg New York, USA, , pp. 35-45.
Issue Date:: 2011

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Field	Value	Language
dc.contributor.author	Wang, L	en_US
dc.contributor.author	He, X	en_US
dc.contributor.author	Du, R	en_US
dc.contributor.author	Jia, W	en_US
dc.contributor.author	Wu, Q	en_US
dc.contributor.author	Yeh, W	en_US
dc.contributor.editor	Kuo-Tien Lee; Wen-Hsiang Tsai; Hong-Yuan Mark Liao; Tsuhan Chen; Jun-Wei Hsieh; Chien-Cheng Tseng	en_US
dc.date	20110105	en_US
dc.date.accessioned	2012-02-02T11:06:38Z
dc.date.available	2012-02-02T11:06:38Z
dc.date.issued	2011	en_US
dc.identifier	2010000317	en_US
dc.identifier.citation	Wang Lin et al. 2011, 'Facial Expression Recognition on Hexagonal Structure Using LBP-Based Histogram Variances', , Springer Berlin Heildelberg New York, USA, , pp. 35-45.	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.other	E1	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16097
dc.description.abstract	In our earlier work, we have proposed an HVF (Histogram Variance Face) approach and proved its effectiveness for facial expression recognition. In this paper, we extend the HVF approach and present a novel approach for facial expression. We take into account the human perspective and understanding of facial expressions. For the first time, we propose to use the Local Binary Pattern (LBP) defined on the hexagonal structure to extract local, dynamic facial features from facial expression images. The dynamic LBP features are used to construct a static image, namely Hexagonal Histogram Variance Face (HHVF), for the video representing a facial expression. We show that the HHVFs representing the same facial expression (e.g., surprise, happy and sadness etc.) are similar no matter if the performers and frame rates are different. Therefore, the proposed facial recognition approach can be utilised for the dynamic expression recognition. We have tested our approach on the well-known Cohn-Kanade AU-Coded Facial Expression database. We have found the improved accuracy of HHVF-based classification compared with the HVF-based approach.	en_US
dc.publisher	Springer Berlin Heildelberg New York	en_US
dc.relation.ispartof	17th International Multimedia Modeling Conference - Advances in Multimedia Modeling (MMM 2011)	en_US
dc.relation.ispartof	Verified OK	en_US
dc.relation.isbasedon	http://dx.doi.org/10.1007/978-3-642-17829-0_4	en_US
dc.subject	Histogram Variance Face - Action Unit - Hexagonal structure - PCA - SVM	en_US
dc.subject.classification	Information Systems	en_US
dc.title	Facial Expression Recognition on Hexagonal Structure Using LBP-Based Histogram Variances	en_US
dc.type	Conference
utslib.location	USA	en_US
utslib.citation.startpage	35	en_US
utslib.citation.endpage	45	en_US
utslib.identifier.org	FEIT.School of Computing and Communications	en_US
utslib.for	080600	en_US
utslib.percentage	000100	en_US
utslib.citation.edition	LNCS 2011	en_US
dc.location.activity	Taipei, Taiwan	en_US
utslib.copyright.status	closed_access

Abstract:

In our earlier work, we have proposed an HVF (Histogram Variance Face) approach and proved its effectiveness for facial expression recognition. In this paper, we extend the HVF approach and present a novel approach for facial expression. We take into account the human perspective and understanding of facial expressions. For the first time, we propose to use the Local Binary Pattern (LBP) defined on the hexagonal structure to extract local, dynamic facial features from facial expression images. The dynamic LBP features are used to construct a static image, namely Hexagonal Histogram Variance Face (HHVF), for the video representing a facial expression. We show that the HHVFs representing the same facial expression (e.g., surprise, happy and sadness etc.) are similar no matter if the performers and frame rates are different. Therefore, the proposed facial recognition approach can be utilised for the dynamic expression recognition. We have tested our approach on the well-known Cohn-Kanade AU-Coded Facial Expression database. We have found the improved accuracy of HHVF-based classification compared with the HVF-based approach.

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http://hdl.handle.net/10453/16097