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Analysis of Variance of Opinion Scores for MPEG-4 Scalable and Advanced Video Coding
Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.ORCID iD: 0000-0002-1730-9026
Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.ORCID iD: 0000-0003-3604-2766
Blekinge Institute of Technology, Faculty of Computing, Department of Creative Technologies.ORCID iD: 0000-0003-3639-9327
2018 (English)In: 2018 12TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND COMMUNICATION SYSTEMS (ICSPCS) / [ed] Wysocki, TA Wysocki, BJ, IEEE , 2018Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we conduct an analysis of variance (ANOVA) on opinion scores for MPEG-4 scalable video coding (SVC) and advanced video coding (AVC) standards. This work resorts on a publicly available database providing opinion scores from subjective experiments for several scenarios such as different bit rates and resolutions. In particular, ANOVA is used for statistical hypothesis testing to compare two or more sets of opinion scores instead of being constrained to pairs of sets of opinion scores as would be the case for t-tests. As the ANOVA tests of the different scenarios are performed for mean opinion scores (MOS), box plots are also provided in order to assess the distribution of the opinion scores around the median. It is shown that the opinion scores given to the reference videos in SVC and AVC for different resolutions are statistically significantly similar regardless of the content. Further, for the opinion scores of the considered database, the ANOVA tests support the hypothesis that AVC generally outperforms SVC although the performance difference may be less pronounced for higher bit rates. This work also shows that additional insights on the results of subjective experiments can be obtained by extending the analysis of opinion scores beyond MOS to ANOVA tests and box plots.

Place, publisher, year, edition, pages
IEEE , 2018.
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:bth-17694DOI: 10.1109/ICSPCS.2018.8631713ISI: 000458665600006Scopus ID: 2-s2.0-85062839973ISBN: 9781538656020 (print)OAI: oai:DiVA.org:bth-17694DiVA, id: diva2:1294296
Conference
12th International Conference on Signal Processing and Communication Systems (ICSPCS), Cairns,DEC 17-19
Part of project
VIATECH- Human-Centered Computing for Novel Visual and Interactive Applications, Knowledge Foundation
Funder
Knowledge Foundation, 20170056Available from: 2019-03-07 Created: 2019-03-07 Last updated: 2021-11-09Bibliographically approved

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Chu, Thi My ChinhZepernick, Hans-JuergenSundstedt, Veronica

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