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컴퓨터 알고리즘 추천에 의한 포토모자이크 기법

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dc.contributor.author전영재-
dc.contributor.author오경수-
dc.date.available2018-05-10T15:05:18Z-
dc.date.created2018-04-17-
dc.date.issued2010-11-
dc.identifier.issn2005-5587-
dc.identifier.urihttp://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/15489-
dc.description.abstractWe propose a new photomosaics method using principle components of candidate photo set. PCA(Principle Component Analysis) reduces dimensions of non-intuitive high dimension data set and allows us to deal the data set more easily. Principle component is a good direction of a basis representing each data according to its distribution. Two data projected onto a certain principal component are similar if their projected position are similar. More principle components provide more accurate comparison between data. We selected the most similar candidate photo to an input photo tile using properties of PCA. Unlike most previous photomosaics methods,photomosaics author can choose candidate photo set and manipulate the number of principle components to change mood of the result of his work. For more active making of photomoasics, we expend room for intervention of author's opinions and propose a method to make various results by a simple way.-
dc.language한국어-
dc.language.isoko-
dc.publisher예술과미디어학회-
dc.relation.isPartOf예술과 미디어-
dc.subjectPhotomosaics-
dc.subjectPrinciple Component Analysis-
dc.subjectReal-time Rendering-
dc.title컴퓨터 알고리즘 추천에 의한 포토모자이크 기법-
dc.title.alternativeA Photomosaics Method by Preference of a Computer Algorithm-
dc.typeArticle-
dc.type.rimsART-
dc.identifier.bibliographicCitation예술과 미디어, v.9, no.2, pp.109 - 117-
dc.identifier.kciidART001536937-
dc.description.journalClass2-
dc.citation.endPage117-
dc.citation.number2-
dc.citation.startPage109-
dc.citation.title예술과 미디어-
dc.citation.volume9-
dc.contributor.affiliatedAuthor오경수-
dc.identifier.urlhttps://www.kci.go.kr/kciportal/ci/sereArticleSearch/ciSereArtiView.kci?sereArticleSearchBean.artiId=ART001536937-
dc.description.isOpenAccessN-
dc.subject.keywordAuthorPhotomosaics-
dc.subject.keywordAuthorPrinciple Component Analysis-
dc.subject.keywordAuthorReal-time Rendering-
dc.description.journalRegisteredClasskci-
dc.description.journalRegisteredClassother-
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