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Non-environment-sensitive facial recognition system using two CCTV cameras

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dc.contributor.author고일주-
dc.contributor.author방그린-
dc.contributor.author정다니엘-
dc.contributor.author김의선-
dc.date.available2018-05-08T00:25:47Z-
dc.date.created2018-04-18-
dc.date.issued2016-11-
dc.identifier.issn1975-0080-
dc.identifier.urihttp://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/5775-
dc.description.abstractWith the rapid growth of the high image quality CCTV monitoring market, research on facial recognition from long as well as short distances is needed. We proposed a non-environment-sensitive hybrid facial recognition system using fixed-format and pan-tilt-zoom cameras. The proposed system enables efficient system load distribution and facial recognition in the transferred images from multiple sites and channels. Furthermore, this system enables the multiple face detection and image processing of multiple CCTV channels. This system can be used for security monitoring in the public areas, and can create a new intellectual video monitoring market. © 2016 SERSC.-
dc.language영어-
dc.language.isoen-
dc.publisherScience and Engineering Research Support Society-
dc.relation.isPartOfInternational Journal of Multimedia and Ubiquitous Engineering-
dc.titleNon-environment-sensitive facial recognition system using two CCTV cameras-
dc.typeArticle-
dc.identifier.doi10.14257/ijmue.2016.11.11.24-
dc.type.rimsART-
dc.identifier.bibliographicCitationInternational Journal of Multimedia and Ubiquitous Engineering, v.11, no.11, pp.281 - 290-
dc.description.journalClass1-
dc.identifier.scopusid2-s2.0-85002374780-
dc.citation.endPage290-
dc.citation.number11-
dc.citation.startPage281-
dc.citation.titleInternational Journal of Multimedia and Ubiquitous Engineering-
dc.citation.volume11-
dc.contributor.affiliatedAuthor고일주-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.subject.keywordAuthorDistributed processing-
dc.subject.keywordAuthorFace detection-
dc.subject.keywordAuthorNon-environment-sensitive facial recognition-
dc.subject.keywordAuthorObject detection-
dc.description.journalRegisteredClassscopus-
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