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DC poleHodnotaJazyk
dc.contributor.authorMliki, Hazar
dc.contributor.authorHammami, Mohamed
dc.contributor.editorSkala, Václav
dc.date.accessioned2018-05-18T12:55:19Z-
dc.date.available2018-05-18T12:55:19Z-
dc.date.issued2016
dc.identifier.citationWSCG '2016: short communications proceedings: The 24th International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision 2016 in co-operation with EUROGRAPHICS: University of West Bohemia, Plzen, Czech RepublicMay 30 - June 3 2016, p. 309-316.en
dc.identifier.isbn978-80-86943-58-9
dc.identifier.issn2464-4617
dc.identifier.uriwscg.zcu.cz/WSCG2016/!!_CSRN-2602.pdf
dc.identifier.urihttp://hdl.handle.net/11025/29718
dc.description.abstractThis paper proposes a novel facial expression recognition method composed of two main steps: offline step and online step. The offline step selects the most salient facial patches using mutual information technique. The online step relies on the already selected patches to identify the facial expression using an SVM classifier. In both steps, the LBP operator was used to extract facial expressions features. Through an extensive experiments on the JAFFE and KANADE databases, we have shown that our method, thanks to the salient selected patches, has the advantage of being much faster with a significant gain in recognition performance.en
dc.format8 s.cs
dc.format.mimetypeapplication/pdf
dc.language.isoenen
dc.publisherVáclav Skala - UNION Agencyen
dc.relation.ispartofseriesWSCG '2016: short communications proceedingsen
dc.rights© Václav Skala - UNION Agencycs
dc.subjectstrojní viděnícs
dc.subjectrozpoznávání výrazu obličejecs
dc.subjectvzájemné informacecs
dc.subjectLBPcs
dc.titleFacial expression recognition using salient facial patchesen
dc.typekonferenční příspěvekcs
dc.typeconferenceObjecten
dc.rights.accessopenAccessen
dc.type.versionpublishedVersionen
dc.subject.translatedmachine visionen
dc.subject.translatedfacial expression recognitionen
dc.subject.translatedmutual informationen
dc.subject.translatedLBPen
dc.type.statusPeer-revieweden
Vyskytuje se v kolekcích:WSCG '2016: Short Papers Proceedings

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