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Title: Quality-aware adaptive delivery of multi-view video
Authors: Ozcinar, Cagri
Ekmekcioglu, Erhan
Kondoz, Ahmet
Keywords: 3D
Multi-view video
Scalable coding
Adaptation of decision strategy
Analysis of dynamic network
Issue Date: 2016
Publisher: © IEEE
Citation: OZCINAR, C., EKMEKCIOGLU, E. and KONDOZ, A., 2016. Quality-aware adaptive delivery of multi-view video. IN: IEEE 41st International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Shanghai, China, 20-25 March 2016, pp. 1397 - 1401.
Abstract: Advances in video coding and networking technologies have paved the way for the Multi-View Video (MVV) streaming. However, large amounts of data and dynamic network conditions result in frequent network congestion, which may prevent video packets from being delivered on time. As a consequence, the 3D viewing experience may be degraded signifi- cantly, unless quality-aware adaptation methods are deployed. There is no research work to discuss the MVV adaptation of decision strategy or provide a detailed analysis of a dynamic network environment. This work addresses the mentioned issues for MVV streaming over HTTP for emerging multi-view displays. In this research work, the effect of various adaptations of decision strategies are evaluated and, as a result, a new quality-aware adaptation method is designed. The proposed method is benefiting from layer based video coding in such a way that high Quality of Experience (QoE) is maintained in a cost-effective manner. The conducted experimental results on MVV streaming using the proposed strategy are showing that the perceptual 3D video quality, under adverse network conditions, is enhanced significantly as a result of the proposed quality-aware adaptation.
Description: © 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.
Version: Accepted for publication
DOI: 10.1109/ICASSP.2016.7471906
URI: https://dspace.lboro.ac.uk/2134/20922
Publisher Link: http://dx.doi.org/10.1109/ICASSP.2016.7471906
ISBN: 9781479999880
Appears in Collections:Conference Papers and Presentations (Loughborough University London)

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