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Facial component detection for efficient facial characteristic point extraction

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dc.contributor.authorOh, J.-S.-
dc.contributor.authorKim, D.-W.-
dc.contributor.authorKim, J.-T.-
dc.contributor.authorYoon, Y.-I.-
dc.contributor.authorChoi, J.-S.-
dc.date.accessioned2023-03-09T00:37:50Z-
dc.date.available2023-03-09T00:37:50Z-
dc.date.issued2005-09-
dc.identifier.issn0302-9743-
dc.identifier.issn1611-3349-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/65490-
dc.description.abstractThis paper proposes an algorithm detecting facial component to efficiently extract the FCP (Facial Characteristic Point). The FCP plays an important role in facial expression representation or recognition. For efficient FCP extraction using image processing, we analyze and improve the conventional algorithms detecting facial components that are the basis of the FCP extraction. The proposed algorithm includes face region detection without the effect of skin-color hair, eye region detection with weighted template, eyebrow region detection using a modified histogram, and mouth region detection using skin characteristics.-
dc.format.extent8-
dc.language영어-
dc.language.isoENG-
dc.publisherSPRINGER-VERLAG BERLIN-
dc.titleFacial component detection for efficient facial characteristic point extraction-
dc.typeArticle-
dc.identifier.doi10.1007/11559573_136-
dc.identifier.bibliographicCitationIMAGE ANALYSIS AND RECOGNITION, v.3656, pp 1125 - 1132-
dc.description.isOpenAccessN-
dc.identifier.wosid000233991100136-
dc.identifier.scopusid2-s2.0-33646000583-
dc.citation.endPage1132-
dc.citation.startPage1125-
dc.citation.titleIMAGE ANALYSIS AND RECOGNITION-
dc.citation.volume3656-
dc.type.docTypeArticle; Proceedings Paper-
dc.publisher.location독일-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaImaging Science & Photographic Technology-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.relation.journalWebOfScienceCategoryImaging Science & Photographic Technology-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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Graduate School of Advanced Imaging Sciences, Multimedia and Film > Department of Imaging Science and Arts > 1. Journal Articles

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