A no reference depth perception assessment metric for 3D video

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dc.contributor.authorYilmaz, G. Nur
dc.date.accessioned2020-06-25T18:12:59Z
dc.date.available2020-06-25T18:12:59Z
dc.date.issued2015
dc.departmentKırıkkale Üniversitesi
dc.descriptionNUR YILMAZ, Gokce/0000-0002-0015-9519
dc.description.abstractRecent technological breakthroughs in 3-Dimensional (3D) video capture, display, coding, transmission, rendering, etc. have led the advances of 3D multimedia applications into the consumer market. However, the effect of these technologies on 3D video Quality of Experience (QoE) has not been thoroughly investigated to speed up the wide-spread proliferation of the 3D video applications in this market. Quality and depth perception assessment of 3D video from the view of end users reflects the most important aspect of 3D video QoE. Therefore, evaluating quality and depth perception of 3D video should be given the utmost attention. Currently, the depth perception assessment of 3D video can only be achieved using time consuming and rigorous subjective assessments due to the lack of reliable and efficient objective metrics. Assessing the depth perception using Full-Reference (FR)/Reduced Reference (RR) objective metrics is not efficient for on the fly 3D video applications due to the requirement of original video/extracted information at the receiver side. Thus, a No Reference (NR) metric, which does not need any original video related information at the receiver side to predict the depth perception, is proposed in this paper. Three important cues (i.e., binocular parallax, lateral motion, and aerial perspective) for Human Visual System (HVS) to perceive the depth of a 3D video are utilized to develop the NR metric. Experimental results devised using the proposed metric prove the effectiveness of it to predict the depth perception.en_US
dc.identifier.citationclosedAccessen_US
dc.identifier.doi10.1007/s11042-014-1945-y
dc.identifier.endpage6950en_US
dc.identifier.issn1380-7501
dc.identifier.issn1573-7721
dc.identifier.issue17en_US
dc.identifier.scopus2-s2.0-84957727865
dc.identifier.scopusqualityQ1
dc.identifier.startpage6937en_US
dc.identifier.urihttps://doi.org/10.1007/s11042-014-1945-y
dc.identifier.urihttps://hdl.handle.net/20.500.12587/6094
dc.identifier.volume74en_US
dc.identifier.wosWOS:000360071800016
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringeren_US
dc.relation.ispartofMultimedia Tools And Applications
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subject3D videoen_US
dc.subjectAerial perspectiveen_US
dc.subjectBinocular parallaxen_US
dc.subjectDepth perceptionen_US
dc.subjectGaussian Mixture Model (GMM)en_US
dc.subjectExpectation Maximization (EM)en_US
dc.subjectQoEen_US
dc.subjectLateral motionen_US
dc.titleA no reference depth perception assessment metric for 3D videoen_US
dc.typeArticle

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