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Adaptive multi-view video delivery using hybrid networking
journal contribution
posted on 2016-03-10, 09:35 authored by Erhan Ekmekcioglu, Cihat G. Gurler, Ahmet Kondoz, A. Murat TekalpMulti-view entertainment is the next step in 3D immersive media networking owing to its improved depth perception and free-viewpoint viewing capability, where users can observe the scene from the desired viewpoint. This paper outlines a delivery system for multi-view plus depth video combining the broadcast and broadband networks. The Digital Video Broadcast (DVB) network is used along with adaptive Peer-to-Peer (P2P) distribution over the Internet to deliver high-volume multimedia to users. The DVB network has been used to deliver part of the 3D service owing to its robustness and wide availability, as a mechanism to guarantee the minimum 3D Quality of Experience (QoE). The developed system brings key contributions in the P2P transport for real-time multimedia delivery, including a user preference-aware adaptation mechanism, adaptive redundant chunk scheduling for robustness, incentives to decrease the load on the content server for improved system scalability, and resynchronisation capability with the DVB transmission. The introduced features are compared to those of some other well-known P2P solutions to highlight the quantitative gains. A subjective testing campaign has also been organised on the developed hybrid platform, which proves the effectiveness of user-aware adaptation over network-based adaptation on a Mean Opinion Score (MOS) scale.
History
School
- Loughborough University London
Published in
IEEE Trans Circuits and Systems for Video TechnologyCitation
EKMEKCIOGLU, E. ... et al., 2017. Adaptive multi-view video delivery using hybrid networking. IEEE Trans Circuits and Systems for Video Technology, 27(6), pp.1313-1325.Publisher
© IEEEVersion
- AM (Accepted Manuscript)
Publisher statement
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/Publication date
2017Notes
© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.ISSN
1051-8215Publisher version
Language
- en