Towards Perceptually Optimized Adaptive Video Streaming-A Realistic Quality of Experience Database

Measuring Quality of Experience (QoE) and integrating these measurements into video streaming algorithms is a multi-faceted problem that fundamentally requires the design of comprehensive subjective QoE databases and objective QoE prediction models. To achieve this goal, we have recently designed th...

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Veröffentlicht in:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 30(2021) vom: 20., Seite 5182-5197
1. Verfasser: Bampis, Christos G (VerfasserIn)
Weitere Verfasser: Li, Zhi, Katsavounidis, Ioannis, Huang, Te-Yuan, Ekanadham, Chaitanya, Bovik, Alan C
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2021
Zugriff auf das übergeordnete Werk:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:Journal Article
Beschreibung
Zusammenfassung:Measuring Quality of Experience (QoE) and integrating these measurements into video streaming algorithms is a multi-faceted problem that fundamentally requires the design of comprehensive subjective QoE databases and objective QoE prediction models. To achieve this goal, we have recently designed the LIVE-NFLX-II database, a highly-realistic database which contains subjective QoE responses to various design dimensions, such as bitrate adaptation algorithms, network conditions and video content. Our database builds on recent advancements in content-adaptive encoding and incorporates actual network traces to capture realistic network variations on the client device. The new database focuses on low bandwidth conditions which are more challenging for bitrate adaptation algorithms, which often must navigate tradeoffs between rebuffering and video quality. Using our database, we study the effects of multiple streaming dimensions on user experience and evaluate video quality and quality of experience models and analyze their strengths and weaknesses. We believe that the tools introduced here will help inspire further progress on the development of perceptually-optimized client adaptation and video streaming strategies. The database is publicly available at http://live.ece.utexas.edu/research/LIVE_NFLX_II/live_nflx_plus.html
Beschreibung:Date Completed 27.05.2021
Date Revised 27.05.2021
published: Print-Electronic
Citation Status PubMed-not-MEDLINE
ISSN:1941-0042
DOI:10.1109/TIP.2021.3073294