Advances In Quality Assessment Of Video Streaming Systems: Algorithms, Methods, Tools

被引:0
作者
Andreopoulos, Yiannis [1 ]
Stejerean, Cosmin [2 ]
机构
[1] iSIZE, Altrincham, Cheshire, England
[2] Meta Platforms Inc, Menlo Pk, CA USA
来源
PROCEEDINGS OF THE 30TH ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA, MM 2022 | 2022年
关键词
quality assessment; video coding; video denoising; datasets;
D O I
10.1145/3503161.3546968
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Quality assessment of video has matured significantly in the last 10 years due to a flurry of relevant developments in academia and industry, with relevant initiatives in VQEG, AOMedia, MPEG, ITU-T P.910, and other standardization and advisory bodies. Most advanced video streaming systems are now clearly moving away from 'good old-fashioned' PSNR and structural similarity type of assessment towards metrics that align better to mean opinion scores from viewers. Several of these algorithms, methods and tools have only been developed in the last 3-5 years and, while they are of significant interest to the research community, their advantages and limitations are not widely known in the research community. This tutorial provides this overview, but also focuses on practical aspects and how to design quality assessment tests that can scale to large datasets.
引用
收藏
页码:7371 / 7371
页数:1
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