Facial expression recognition based on anatomy

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dc.authorid0000-0003-0298-0690
dc.authorid0000-0001-6282-6703
dc.contributor.authorEskil, Mustafa Taneren_US
dc.contributor.authorBenli, Kristin Surpuhien_US
dc.date.accessioned2015-01-15T23:02:52Z
dc.date.available2015-01-15T23:02:52Z
dc.date.issued2014-02
dc.departmentIşık Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.departmentIşık University, Faculty of Engineering, Department of Computer Engineeringen_US
dc.description.abstractIn this study, we propose a novel approach to facial expression recognition that capitalizes on the anatomical structure of the human face. We model human face with a high-polygon wireframe model that embeds all major muscles. Influence regions of facial muscles are estimated through a semi-automatic customization process. These regions are projected to the image plane to determine feature points. Relative displacement of each feature point between two image frames is treated as an evidence of muscular activity. Feature point displacements are projected back to the 3D space to estimate the new coordinates of the wireframe vertices. Muscular activities that would produce the estimated deformation are solved through a least squares algorithm. We demonstrate the representative power of muscle force based features on three classifiers; NB, SVM and Adaboost Ability to extract muscle forces that compose a facial expression will enable detection of subtle expressions, replicating an expression on animated characters and exploration of psychologically unknown mechanisms of facial expressions.en_US
dc.description.versionPublisher's Versionen_US
dc.identifier.citationEskil, M. T. & Benli, K. S. (2014). Facial expression recognition based on anatomy. Computer Vision and Image Understanding, 119, 1-14. doi:10.1016/j.cviu.2013.11.002en_US
dc.identifier.doi10.1016/j.cviu.2013.11.002
dc.identifier.endpage14
dc.identifier.issn1077-3142
dc.identifier.issn1090-235X
dc.identifier.scopus2-s2.0-84890404701
dc.identifier.scopusqualityQ1
dc.identifier.startpage1
dc.identifier.urihttps://hdl.handle.net/11729/549
dc.identifier.urihttp://dx.doi.org/10.1016/j.cviu.2013.11.002
dc.identifier.volume119
dc.identifier.wosWOS:000330752700001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.indekslendigikaynakScience Citation Index Expanded (SCI-EXPANDED)en_US
dc.institutionauthorEskil, Mustafa Taneren_US
dc.institutionauthorBenli, Kristin Surpuhien_US
dc.institutionauthorid0000-0003-0298-0690
dc.institutionauthorid0000-0001-6282-6703
dc.language.isoenen_US
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.publisherAcademic Press Inc Elsevier Scienceen_US
dc.relation.ispartofComputer Vision and Image Understandingen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectFacial anatomyen_US
dc.subjectMuscle forceen_US
dc.subjectFeaturesen_US
dc.subjectFacial action coding systemen_US
dc.subjectActive appearance modelsen_US
dc.subjectRobust face trackingen_US
dc.subjectInformation fusionen_US
dc.subjectMotionen_US
dc.subjectVideoen_US
dc.subjectImagesen_US
dc.subjectFace recognitionen_US
dc.subjectAdaptive boostingen_US
dc.subjectGesture recognitionen_US
dc.subjectMuscleen_US
dc.subjectFacial expression recognitionen_US
dc.subjectLeast squares algorithmen_US
dc.subjectRelative displacementen_US
dc.titleFacial expression recognition based on anatomyen_US
dc.typeArticleen_US
dspace.entity.typePublication

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