Scene Detection via Depth Maps Of 3 Dimensional Videos

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dc.contributor.authorBayrak, Huseyin
dc.contributor.authorNur Yilmaz, Gokce
dc.date.accessioned2020-06-25T18:23:27Z
dc.date.available2020-06-25T18:23:27Z
dc.date.issued2017
dc.departmentKırıkkale Üniversitesi
dc.description25th Signal Processing and Communications Applications Conference (SIU) -- MAY 15-18, 2017 -- Antalya, TURKEY
dc.description.abstractScene detection via processing of multimedia data is a significant research area for the advancement of the video technologies and applications. Currently, the scene detection is mostly performed manually. Thus, it is time consuming and costly. Therefore, it is important to develop algorithms that can automatically segment scenes to support the advancement of these technologies and applications. With the wide-spread utilization of the 3 Dimensional (3D) videos, researchers working in the field of the video scene detection start using them in this field as well. However, there is still a gap in the application of the scene detection algorithms to Depth Maps (DMs) that are a part of the 3D video and important for temporal video scene detection. In this study, dominant clusters and K-means method is proposed to detect the temporal 3D video segments using the DMs. The experimental studies performed using the scene detection method present that the video scenes can be edited efficiently without human assistance. Moreover, unlike similar studies in the literature, the proposed method can provide successful results on video sequences thanks to the dominant clusters and the K-means clustering approach utilized.en_US
dc.description.sponsorshipTurk Telekom, Arcelik A S, Aselsan, ARGENIT, HAVELSAN, NETAS, Adresgezgini, IEEE Turkey Sect, AVCR Informat Technologies, Cisco, i2i Syst, Integrated Syst & Syst Design, ENOVAS, FiGES Engn, MS Spektral, Istanbul Teknik Univen_US
dc.identifier.citationclosedAccessen_US
dc.identifier.isbn978-1-5090-6494-6
dc.identifier.issn2165-0608
dc.identifier.scopus2-s2.0-85026311436
dc.identifier.scopusqualityN/A
dc.identifier.urihttps://hdl.handle.net/20.500.12587/7105
dc.identifier.wosWOS:000413813100154
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isotr
dc.publisherIeeeen_US
dc.relation.ispartof2017 25Th Signal Processing And Communications Applications Conference (Siu)
dc.relation.ispartofseriesSignal Processing and Communications Applications Conference
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subject3D Videoen_US
dc.subjectDominant Clustersen_US
dc.subjectK-Meansen_US
dc.subjectClusteringen_US
dc.subjectDepth Mapen_US
dc.subjectVideo Scene Detectionen_US
dc.titleScene Detection via Depth Maps Of 3 Dimensional Videosen_US
dc.typeConference Object

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