Εμφάνιση απλής εγγραφής

dc.creatorKoziri M., Papadopoulos P., Tziritas N., Dadaliaris A.N., Loukopoulos T., Stamoulis G.I.en
dc.date.accessioned2023-01-31T08:46:51Z
dc.date.available2023-01-31T08:46:51Z
dc.date.issued2016
dc.identifier10.1109/SMAP.2016.7753380
dc.identifier.isbn9781509052455
dc.identifier.urihttp://hdl.handle.net/11615/75484
dc.description.abstractThe ever increasing number of video uploads in social media platforms, together with the incorporation of live video broadcasts and a growing demand for higher video resolution, will likely pose the most significant performance challenge for social media providers in the years to come. The current state of the art in most social media platforms, involves videos in H.264/AVC format. However, recent advances in video encoding such as the HEVC standard offer better compression ratios compared to H.264/AVC at the expense of higher computational demands. As HEVC is gradually replacing the old standard, the possibility of reducing bandwidth consumption and server load by using the more efficient compression scheme can't be overlooked. In this paper we propose a framework to tackle the challenges of adopting HEVC as well as high resolution videos in social media platforms. © 2016 IEEE.en
dc.language.isoenen
dc.sourceProceedings - 11th International Workshop on Semantic and Social Media Adaptation and Personalization, SMAP 2016en
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85006830393&doi=10.1109%2fSMAP.2016.7753380&partnerID=40&md5=96ec0968b106b64edbb736455f07c4a1
dc.subjectBandwidth compressionen
dc.subjectEncoding (symbols)en
dc.subjectMotion Picture Experts Group standardsen
dc.subjectSchedulingen
dc.subjectSemanticsen
dc.subjectSocial networking (online)en
dc.subjectVideo signal processingen
dc.subjectBandwidth consumptionen
dc.subjectCompression schemeen
dc.subjectComputational demandsen
dc.subjectHEVCen
dc.subjectPerformance challengesen
dc.subjectSocial mediaen
dc.subjectSocial media platformsen
dc.subjectVideo encodingsen
dc.subjectImage compressionen
dc.subjectInstitute of Electrical and Electronics Engineers Inc.en
dc.titleA framework for scheduling the encoding of multiple smart user videosen
dc.typeconferenceItemen


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