QoE model of scalable MDC stereoscopic video over IP networks

Charalampos Mysirlidis, Ilias Politis, Tasos Dagiuklas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

Multiple description coding and path diversity is known to improve the perceptual quality of the received video. This paper considers a machine learning based technique to predict the perceived video quality, in terms of Mean Opinion Score for MDC Stereoscopic video. The perceived experience is expressed as a function of the three-dimensional video representation (color-plus-depth and left-right), the path diversity characterized by asymmetric packet losses between two available paths and the interpolation using a single description delivered over a reliable link as opposed to using multiple unreliable delivered descriptions.

Original languageEnglish
Title of host publication2014 IEEE International Conference on Image Processing, ICIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages66-70
Number of pages5
ISBN (Electronic)9781479957514
DOIs
Publication statusPublished - 28 Jan 2014
Externally publishedYes

Publication series

Name2014 IEEE International Conference on Image Processing, ICIP 2014

Bibliographical note

Publisher Copyright:
© 2014 IEEE.

Keywords

  • C4.5
  • color-plus-depth
  • left-right
  • MDC
  • MOS

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