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Assessment of QoE for Video and Audio in WebRTC Applications Using Full-Reference Models

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Department of Telematic Engineering, Universidad Carlos III de Madrid, Avenida de la Universidad 30, 28911 Leganés, Spain
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Department of Computer Science, Computer Architecture, Computer Languages & Information Systems, Statistics & Operational Research, Universidad Rey Juan Carlos, Calle Tulipán S/N, 28933 Móstoles, Spain
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School of Computer Science, University College Dublin, Dublin 4, Ireland
*
Author to whom correspondence should be addressed.
Electronics 2020, 9(3), 462; https://doi.org/10.3390/electronics9030462
Received: 11 February 2020 / Revised: 3 March 2020 / Accepted: 6 March 2020 / Published: 10 March 2020
(This article belongs to the Section Computer Science & Engineering)
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. View Full-Text
Keywords: QoE; WebRTC; video quality; audio quality; full-reference QoE; WebRTC; video quality; audio quality; full-reference
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García, B.; Gortázar, F.; Gallego, M.; Hines, A. Assessment of QoE for Video and Audio in WebRTC Applications Using Full-Reference Models. Electronics 2020, 9, 462.

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