• DocumentCode
    34375
  • Title

    Optimized MVC Prediction Structures for Interactive Multiview Video Streaming

  • Author

    De Abreu, A. ; Frossard, Pascal ; Pereira, Fernando

  • Author_Institution
    Signal Process. Lab. (LTS4), Ecole Politechnique Fed. de Lausanne (EPFL), Lausanne, Switzerland
  • Volume
    20
  • Issue
    6
  • fYear
    2013
  • fDate
    Jun-13
  • Firstpage
    603
  • Lastpage
    606
  • Abstract
    The Multiview Video Coding (MVC) standard efficiently compresses multiview video by considering spatial, temporal and interview correlations. This letter studies the impact of the MVC interview prediction structure on both the transmission and the overall coding rates for an interactive multiview video streaming system, considering both unicast and multicast scenarios, with the user interactive behavior represented by some view-popularity model. We propose a method to identify the optimal prediction structure minimizing the visual distortion, given some storage and link capacities constraints. Simulation results confirm that the optimal prediction structure results from a non-trivial tradeoff between the system constraints, the transmission model and the views´ popularity.
  • Keywords
    data compression; interactive video; video coding; video streaming; MVC standard; coding rate; interactive multiview video streaming system; interview correlation; link capacity constraint; multiview video coding standard; multiview video compression; optimized MVC interview prediction structures; spatial correlation; storage capacity constraint; system constraints; temporal correlation; transmission model; transmission rate; user interactive behavior; view popularity; view-popularity model; visual distortion; Encoding; Interviews; Optimization; Servers; Streaming media; Unicast; Video coding; Interactive multiview video streaming (IMVS); multicast; multiview video coding (MVC); popularity model; prediction structure; unicast;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2013.2259815
  • Filename
    6507571