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Quality of Experience Assessment for HTTP Based Adaptive Video Streaming

ARSENOVIC, M. See more information about ARSENOVIC, M. on SCOPUS See more information about ARSENOVIC, M. on IEEExplore See more information about ARSENOVIC, M. on Web of Science, RIMAC-DRLJE, S. See more information about RIMAC-DRLJE, S. on SCOPUS See more information about RIMAC-DRLJE, S. on SCOPUS See more information about RIMAC-DRLJE, S. on Web of Science
 
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Download PDF pdficon (1,205 KB) | Citation | Downloads: 717 | Views: 795

Author keywords
hybrid metrics, HTTP adaptive streaming, LIVE-NFLX-II database, Quality of Experience, video quality metrics

References keywords
quality(34), video(20), streaming(17), experience(12), assessment(12), adaptive(11), image(10), bovik(7), service(5), multimedia(5)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2023-02-28
Volume 23, Issue 1, Year 2023, On page(s): 33 - 42
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2023.01004
Web of Science Accession Number: 000937345700004
SCOPUS ID: 85150182647

Abstract
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The expected optimal outcome of users' video quality requirements should be the best Quality of Experience (QoE). Integrating and evaluating QoE in a video streaming system is a rather complex process that requires a comprehensive design of subjective databases and video quality metrics. The goal of this paper is to examine the parameters that affect QoE in adaptive video streaming, as well as metrics for evaluating video quality. The paper reviews and analyses 21 QoE metrics, out of which 4 are general video evaluation metrics, 7 are adaptive video streaming evaluation metrics, and 10 are hybrid metrics and their usability for QoE measurement for HTTP-based adaptive streaming (HAS). The LIVE-NFLX-II database is used to compare the metrics. The hybrid metrics that combine one of the full reference metrics with the no-reference metric that uses a combination of average bitrate, rebuffering percentage, and average bitrate switching magnitude, has yielded the best correlations with the subjective quality ratings.


References | Cited By  «-- Click to see who has cited this paper

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References Weight

Web of Science® Citations for all references: 37,221 TCR
SCOPUS® Citations for all references: 45,112 TCR

Web of Science® Average Citations per reference: 866 ACR
SCOPUS® Average Citations per reference: 1,049 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-05-17 15:37 in 189 seconds.




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