Yaqoob, Abid, Bi, Ting and Muntean, Gabriel-Miro (2020) A Survey on Adaptive 360° Video Streaming: Solutions, Challenges and Opportunities. IEEE Communications Surveys & Tutorials, 22 (4). pp. 2801-2838. ISSN 2373-745X
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Abstract
Omnidirectional or 360° video is increasingly being used, mostly due to the latest advancements in immersive Virtual Reality (VR) technology. However, its wide adoption is hindered by the higher bandwidth and lower latency requirements than associated with traditional video content delivery. Diverse researchers propose and design solutions that help support an immersive visual experience of 360° video, primarily when delivered over a dynamic network environment. This paper presents the state-of-the-art on adaptive 360° video delivery solutions considering end-to-end video streaming in general and then specifically of 360° video delivery. Current and emerging solutions for adaptive 360° video streaming, including viewport-independent, viewport-dependent, and tile-based schemes are presented. Next, solutions for network-assisted unicast and multicast streaming of 360° video content are discussed. Different research challenges for both on-demand and live 360° video streaming are also analyzed. Several proposed standards and technologies and top international research projects are then presented. We demonstrate the ongoing standardization efforts for 360° media services that ensure interoperability and immersive media deployment on a massive scale. Finally, the paper concludes with a discussion about future research opportunities enabled by 360° video.
Item Type: | Article |
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Additional Information: | Cite as: A. Yaqoob, T. Bi and G. -M. Muntean, "A Survey on Adaptive 360° Video Streaming: Solutions, Challenges and Opportunities," in IEEE Communications Surveys & Tutorials, vol. 22, no. 4, pp. 2801-2838, Fourthquarter 2020, doi: 10.1109/COMST.2020.3006999. |
Keywords: | 360◦ video streaming; virtual reality; HTTP adaptive streaming; MPEG-DASH; video tiling; viewport prediction; quality assessment; standards; |
Academic Unit: | Faculty of Science and Engineering > Maynooth International Engineering College Faculty of Science and Engineering > Computer Science Faculty of Science and Engineering > Research Institutes > Hamilton Institute |
Item ID: | 15659 |
Identification Number: | 10.1109/COMST.2020.3006999 |
Depositing User: | Ting Bi |
Date Deposited: | 11 Mar 2022 14:48 |
Journal or Publication Title: | IEEE Communications Surveys & Tutorials |
Publisher: | IEEE |
Refereed: | Yes |
Related URLs: | |
URI: | https://mu.eprints-hosting.org/id/eprint/15659 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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