1-s2.0-S2215098614000251-main.pdf (2.59 MB)
Download file

3D video bit rate adaptation decision taking using ambient illumination context

Download (2.59 MB)
journal contribution
posted on 07.02.2017, 11:43 by G. Nur Yilmaz, Hemantha Kodikara Arachchi, Safak DoganSafak Dogan, Ahmet KondozAhmet Kondoz
3-Dimensional (3D) video adaptation decision taking is an open field in which not many researchers have carried out investigations yet compared to 3D video display, coding, etc. Moreover, utilizing ambient illumination as an environmental context for 3D video adaptation decision taking has particularly not been studied in literature to date. In this paper, a user perception model, which is based on determining perception characteristics of a user for a 3D video content viewed under a particular ambient illumination condition, is proposed. Using the proposed model, a 3D video bit rate adaptation decision taking technique is developed to determine the adapted bit rate for the 3D video content to maintain 3D video quality perception by considering the ambient illumination condition changes. Experimental results demonstrate that the proposed technique is capable of exploiting the changes in ambient illumination level to use network resources more efficiently without sacrificing the 3D video quality perception.

History

School

  • Loughborough University London

Published in

Engineering Science and Technology, an International Journal

Volume

17

Issue

3

Pages

105 - 115

Citation

NUR YILMAZ, G. ... et al., 2014. 3D video bit rate adaptation decision taking using ambient illumination context. Engineering Science and Technology, an International Journal, 17(3), pp. 105-115.

Publisher

© Karabuk University. Published by Elsevier

Version

VoR (Version of Record)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 Unported (CC BY-NC-ND 3.0) licence. Full details of this licence are available at: http://creativecommons.org/licenses/by-nc-nd/3.0/

Publication date

2014

Notes

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 3.0 Unported Licence NonCommercial-No Derivs (CC BY-NC-ND). Full details of this licence are available at: http://creativecommons.org/licenses/by-nc-nd/3.0/

ISSN

2215-0986

Language

en

Usage metrics

Categories

Exports