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dc.contributor.authorAl-dahoud, Ahmad*
dc.contributor.authorUgail, Hassan*
dc.date.accessioned2019-03-01T14:51:32Z
dc.date.available2019-03-01T14:51:32Z
dc.date.issued2018
dc.identifier.citationAl-dahoud A and Ugail H (2018) Computational analysis of smile weight distribution across the face for accurate distinction between genuine and posed smiles. In: 2018 International Conference on Cyberworlds (CW). 3-5 Oct 2018, Singapore. 191-198.en_US
dc.identifier.urihttp://hdl.handle.net/10454/16871
dc.descriptionYesen_US
dc.description.abstractIn this paper, we report the results of our recent research into the understanding of the exact distribution of a smile across the face, especially the distinction in the weight distribution of a smile between a genuine and a posed smile. To do this, we have developed a computational framework for the analysis of the dynamic motion of various parts of the face during a facial expression, in particular, for the smile expression. The heart of our dynamic smile analysis framework is the use of optical flow intensity variation across the face during a smile. This can be utilised to efficiently map the dynamic motion of individual regions of the face such as the mouth, cheeks and areas around the eyes. Thus, through our computational framework, we infer the exact distribution of weights of the smile across the face. Further, through the utilisation of two publicly available datasets, namely the CK+ dataset with 83 subjects expressing posed smiles and the MUG dataset with 35 subjects expressing genuine smiles, we show there is a far greater activity or weight distribution around the regions of the eyes in the case of a genuine smile.en_US
dc.description.sponsorshipSupported in part by the European Union's Horizon 2020 Programme H2020-MSCA-RISE-2017, under the project PDE-GIR with grant number 778035.en_US
dc.language.isoenen_US
dc.rights© 2018 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.
dc.subjectSmile analysisen_US
dc.subjectGenuine smilesen_US
dc.subjectOptical flowen_US
dc.subjectFaceen_US
dc.subjectHeuristic algorithmsen_US
dc.subjectMouthen_US
dc.subjectMusclesen_US
dc.subjectApproximation algorithmsen_US
dc.subjectDynamicsen_US
dc.titleComputational analysis of smile weight distribution across the face for accurate distinction between genuine and posed smilesen_US
dc.status.refereedYesen_US
dc.date.Accepted2018
dc.date.application2018
dc.typeConference paperen_US
dc.type.versionAccepted manuscripten_US
dc.identifier.doihttps://doi.org/10.1109/CW.2018.00044
refterms.dateFOA2019-03-04T09:53:10Z


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