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

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dc.contributor.author Wang Lin en_US
dc.contributor.author He Xiangjian en_US
dc.contributor.author Du Ruo en_US
dc.contributor.author Jia Wenjing en_US
dc.contributor.author Wu Qiang en_US
dc.contributor.author Yeh Wei-Chang 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.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.language en_US
dc.publisher Springer Berlin Heildelberg New York en_US
dc.relation.isbasedon http://dx.doi.org/10.1007/978-3-642-17829-0_4 en_US
dc.title Facial Expression Recognition on Hexagonal Structure Using LBP-Based Histogram Variances en_US
dc.parent 17th International Multimedia Modeling Conference - Advances in Multimedia Modeling (MMM 2011) en_US
dc.journal.volume en_US
dc.journal.number en_US
dc.publocation USA en_US
dc.identifier.startpage 35 en_US
dc.identifier.endpage 45 en_US
dc.cauo.name FEIT.School of Computing and Communications en_US
dc.conference Verified OK en_US
dc.for 080600 en_US
dc.personcode 0000064937;990421;10253654;044299;000748;106463 en_US
dc.percentage 000100 en_US
dc.classification.name Information Systems en_US
dc.classification.type FOR-08 en_US
dc.edition LNCS 2011 en_US
dc.custom International Multimedia Modeling Conference - Advances in Multimedia Modeling en_US
dc.date.activity 20110105 en_US
dc.location.activity Taipei, Taiwan en_US
dc.description.keywords Histogram Variance Face - Action Unit - Hexagonal structure - PCA - SVM en_US
dc.staffid en_US


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