Assessment of QoE for video and audio in WebRTC applications using full-reference models

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Show simple item record García Gutiérrez, Boni Gortázar, Francisco Gallego, Micael Hines, Andrew 2021-04-14T09:22:55Z 2021-04-14T09:22:55Z 2020-03-10
dc.identifier.bibliographicCitation García B., Gortázar, F., Gallego, M. & Hines A. (2020). Assessment of QoE for video and audio in WebRTC applications using full-reference models. Electronics 2020, 9(3), 462.
dc.identifier.issn 2079-9292
dc.description.abstract WebRTC is a set of standard technologies that allows exchanging video and audio in real time on the Web. As with other media-related applications, the user-perceived audiovisual quality can be estimated using Quality of Experience (QoE) measurements. This paper analyses the behavior of different objective Full-Reference (FR) models for video and audio in WebRTC applications. FR models calculate the video and audio quality by comparing some original media reference with the degraded signal. To compute these models, we have created an open-source benchmark in which different types of reference media inputs are sent browser to browser while simulating different kinds of network conditions in terms of packet loss and jitter. Our benchmark provides recording capabilities of the impairment WebRTC streams. Then, we use different existing FR metrics for video (VMAF, VIFp, SSIM, MS-SSIM, PSNR, PSNR-HVS, and PSNR-HVS-M) and audio (PESQ, ViSQOL, and POLQA) recordings together with their references. Moreover, we use the same recordings to carry out a subjective analysis in which real users rate the video and audio quality using a Mean Opinion Score (MOS). Finally, we calculate the correlations between the objective and subjective results to find the objective models that better correspond with the subjective outcome, which is considered the ground truth QoE. We find that some of the studied objective models, such as VMAF, VIFp, and POLQA, show a strong correlation with the subjective results in packet loss scenarios.
dc.description.sponsorship This work has been supported by the European Commission under project ElasTest (H2020-ICT-10-2016, GA-731535); by the Regional Government of Madrid (CM) under project EDGEDATA-CM (P2018/TCS-4499) cofunded by FSE and FEDER; by the Spanish Government under projects LERNIM (RTC-2016-4674-7) and BugBirth (RTI2018-101963-B-I00) cofunded by the Ministry of Economy and Competitiveness, FEDER, and AEI; and by Science Foundation Ireland (SFI) cofunded under the European Regional Development Fund under grant number 12/RC/2289_P2 and grant number SFI/12/RC/2077.
dc.format.extent 23
dc.language.iso eng
dc.publisher MDPI
dc.rights © 2020 by the authors.
dc.rights Atribución 3.0 España
dc.subject.other Audio quality
dc.subject.other Full-reference
dc.subject.other QoE
dc.subject.other Video quality
dc.subject.other WebRTC
dc.title Assessment of QoE for video and audio in WebRTC applications using full-reference models
dc.type article
dc.subject.eciencia Telecomunicaciones
dc.rights.accessRights openAccess
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/731535/Elas Test
dc.relation.projectID Comunidad de Madrid. P2018/TCS-4499
dc.relation.projectID Gobierno de España. RTC-2016-4674-7
dc.relation.projectID Gobierno de España. RTI2018-101963-B-I00
dc.type.version publishedVersion
dc.identifier.publicationfirstpage 1
dc.identifier.publicationissue 462
dc.identifier.publicationlastpage 23
dc.identifier.publicationtitle Electronics
dc.identifier.publicationvolume 9(3)
dc.identifier.uxxi AR/0000025590
dc.contributor.funder European Commission
dc.contributor.funder Ministerio de Ciencia e Innovación (España)
dc.affiliation.dpto UC3M. Departamento de Ingeniería Telemática
dc.affiliation.grupoinv UC3M. Grupo de Investigación: Aplicaciones y Servicios Telemáticos (GAST)
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