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Stagemix video generation using face and body keypoints detection

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dc.contributor.authorJung, Minjoon-
dc.contributor.authorLee, Seunghyun-
dc.contributor.authorSim, Eun Seon-
dc.contributor.authorJo, Min Ho-
dc.contributor.authorLee, Yu Jin-
dc.contributor.authorChoi, Hye Bin-
dc.contributor.authorKwon, Junseok-
dc.date.accessioned2022-05-19T10:40:29Z-
dc.date.available2022-05-19T10:40:29Z-
dc.date.issued2022-11-
dc.identifier.issn1380-7501-
dc.identifier.issn1432-1882-
dc.identifier.urihttps://scholarworks.bwise.kr/cau/handle/2019.sw.cau/57824-
dc.description.abstractPlaying multiple stage videos of a particular singer as if they are one is called Stagemix video. The consumption of video media has increased recently, and the demand for video editing has also increased. Stagemix videos have gained popularity in various communities, and a number of YouTubers who upload videos with cross-cuts are appearing. In this work, we introduce a novel task, Stagemix video generation. Stagemix video generation requires considerable time and skillful editing skills. To address this, we suggest a method of auto-generating Stagemix video, a novel technique that plays multiple stage videos of a particular singer as if they are one. Our novel methods automatically generate a Stagemix video and improve performance with face or body keypoints which is extracted by CNN-based extractor. Quantitative differences between frames and creation time show that our methods effectively produce a natural video.-
dc.format.extent12-
dc.language영어-
dc.language.isoENG-
dc.publisherSPRINGER-
dc.titleStagemix video generation using face and body keypoints detection-
dc.typeArticle-
dc.identifier.doi10.1007/s11042-022-13103-8-
dc.identifier.bibliographicCitationMULTIMEDIA TOOLS AND APPLICATIONS, v.81, no.27, pp 38531 - 38542-
dc.description.isOpenAccessN-
dc.identifier.wosid000787139200004-
dc.identifier.scopusid2-s2.0-85128811396-
dc.citation.endPage38542-
dc.citation.number27-
dc.citation.startPage38531-
dc.citation.titleMULTIMEDIA TOOLS AND APPLICATIONS-
dc.citation.volume81-
dc.type.docTypeArticle-
dc.publisher.location네델란드-
dc.subject.keywordAuthorPose estimation-
dc.subject.keywordAuthorStagemix video-
dc.subject.keywordAuthorVideo preprocessing-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Information Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Software Engineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Theory & Methods-
dc.relation.journalWebOfScienceCategoryEngineering, Electrical & Electronic-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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소프트웨어대학 (소프트웨어학부)
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