Loughborough University
Browse

File(s) under permanent embargo

Reason: This item is currently closed access.

Adaptive streaming of multi-view video over P2P networks

journal contribution
posted on 2016-04-22, 13:45 authored by S. Sedef Savas, C. Goktug Gurler, A. Murat Tekalp, Erhan Ekmekcioglu, Stewart T. Worrall, Ahmet Kondoz
In this paper, we propose a novel solution for the adaptive streaming of 3D representations in the form of multi-view video by utilizing P2 Poverlay networks to assist the media delivery and minimize the bandwidth requirement at the server side. Adaptation to diverse network conditions is performed regarding the features of human perception to maximize the perceived 3D. We have performed subjective tests to characterize these features and determined the best adaptation method to achieve the highest possible perceived quality. Moreover, we provide a novel method for mapping from scalable video elementary stream to torrent-liked at a chunks for adaptive video streaming and provide an optimized windowing mechanism that ensures timely delivery of the content over yanlıs gibi. The paper also describes techniques generating scalable video chunks and methods for determining system parameters such as chunksize and window length.

Funding

This work was supported under the FP7 STREP Project DIOMEDE

History

School

  • Loughborough University London

Published in

Signal Processing: Image Communication

Volume

27

Issue

5

Pages

522 - 531

Citation

SEDEF SAVAS, S. ...et al., 2012. Adaptive streaming of multi-view video over P2P networks. Signal Processing: Image Communication, 27(5), pp. 522-531.

Publisher

© Elsevier

Version

  • VoR (Version of Record)

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

2012

Notes

This paper is in closed access.

ISSN

0923-5965

Language

  • en

Usage metrics

    Loughborough Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC