5th International Mobile Multimedia Communications Conference

Research Article

Content classification-based and QoE-driven video send bitrate adaptation scheme

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        author={Asiya  Khan and Lingfen  Sun and Emmanuel  Jammeh and Emmanuel  Ifeachor},
        title={Content classification-based and QoE-driven video send bitrate adaptation scheme},
        proceedings={5th International Mobile Multimedia Communications Conference},
        keywords={Content classification Video Send Bitrate (SBR) PSNR QoE.},
  • Asiya Khan
    Lingfen Sun
    Emmanuel Jammeh
    Emmanuel Ifeachor
    Year: 2010
    Content classification-based and QoE-driven video send bitrate adaptation scheme
    DOI: 10.4108/ICST.MOBIMEDIA2009.7687
Asiya Khan1,*, Lingfen Sun1,*, Emmanuel Jammeh1,*, Emmanuel Ifeachor1,*
  • 1: Centre of Signal Processing and Multimedia Communication, School of Computing, Communications and Electronics, University of Plymouth, Drake, Circus, Plymouth PL4 8AA, UK. +44 (0) 1752 586213
*Contact email: asiya.khan@plymouth.ac.uk, l.sun@plymouth.ac.uk, emmanuel.jammeh@plymouth.ac.uk, e.ifeachor@plymouth.ac.uk


Initial video quality requirement is not well understood and content providers usually send video at the highest send bitrate resulting in over-provisioning. The main aim of this paper is to present a new scheme that can adapt video send bitrate according to the dynamics of the content and the user's Quality of Experience (QoE) requirement at the pre-encoding stage. Contents are classified based on their spatio-temporal feature extraction. Video quality is predicted in terms of the Peak-Signal-to-Noise-Ratio (PSNR). Statistical analysis of the experimental results confirms that the proposed adaptation scheme performs well for all content types and hence, improves the perceived end-to-end video quality. The proposed scheme makes it possible for content providers to achieve an optimum streaming scheme (with an appropriate send bitrate) suitable for the content type for a requested QoE.