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dc.contributor.authorZerman, Emin
dc.contributor.authorKonuk, Baris
dc.contributor.authorNur, Gokce
dc.contributor.authorAkar, Gozde Bozdagi
dc.date.accessioned2020-06-25T18:12:32Z
dc.date.available2020-06-25T18:12:32Z
dc.date.issued2014
dc.identifier.isbn978-1-4799-5751-4
dc.identifier.issn1522-4880
dc.identifier.urihttps://hdl.handle.net/20.500.12587/5956
dc.descriptionIEEE International Conference on Image Processing (ICIP) -- OCT 27-30, 2014 -- Paris, FRANCEen_US
dc.descriptionB. Akar, Gozde/0000-0002-4227-5606; NUR YILMAZ, Gokce/0000-0002-0015-9519en_US
dc.descriptionWOS: 000370063600121en_US
dc.description.abstractThe increasing demand for streaming video raises the need for flexible and easily implemented Video Quality Assessment (VQA) metrics. Although there are different VQA metrics, most of these are either Full-Reference (FR) or Reduced-Reference (RR). Both FR and RR metrics bring challenges for on-the-fly multimedia systems due to the necessity of additional network traffic for reference data. No-eference (NR) video metrics, on the other hand, as the name suggests, are much more flexible for user-end applications. This introduces a need for robust and efficient NR VQA metrics. In this paper, an NR VQA metric considering spatiotemporal information, bit rate, and packet loss rate characteristics of a video content is proposed. The proposed metric is evaluated on EPFL-PoliMI dataset, which includes different video content characteristics. The experimental results show that the proposed metric is a robust and accurate NR VQA metric towards diverse video content characteristics.en_US
dc.description.sponsorshipIEEEen_US
dc.language.isoengen_US
dc.publisherIeeeen_US
dc.relation.ispartofseriesIEEE International Conference on Image Processing ICIP
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectQuality of experience (QoE)en_US
dc.subjectno-reference metricen_US
dc.subjectvideo quality assessment (VQA)en_US
dc.subjectnetwork conditionen_US
dc.subjectvideo characteristicsen_US
dc.titleA PARAMETRIC VIDEO QUALITY MODEL BASED ON SOURCE AND NETWORK CHARACTERISTICSen_US
dc.typeconferenceObjecten_US
dc.contributor.departmentKırıkkale Üniversitesien_US
dc.identifier.startpage595en_US
dc.identifier.endpage599en_US
dc.relation.journal2014 Ieee International Conference On Image Processing (Icip)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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