• DocumentCode
    3264536
  • Title

    Fast MVC prediction structure selection 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
  • fYear
    2013
  • fDate
    8-11 Dec. 2013
  • Firstpage
    169
  • Lastpage
    172
  • Abstract
    Multiview Video Coding (MVC) has been developed to efficiently compress a set of camera views by exploiting the spatial, temporal and interview correlations among images of the same scene. However, the resulting compressed data has a lot of prediction coding dependencies, which may not suit interactive multiview video streaming (IMVS) systems, where only one view is requested at a time by the end-user. This paper proposes a fast selection mechanism for effective interview prediction structure (PS) in IMVS while minimizing the point-to-point transmission rate, given some storage and visual distortion constraints, and a user interactive behavior model. Simulation results show that our novel fast MVC PS selection algorithm has high efficiency with low computational complexity that is reduced by more than 40% in comparison to the exhaustive searching benchmark.
  • Keywords
    computational complexity; correlation methods; interactive video; video coding; video streaming; IMVS; MVC prediction structure selection; PS; computational complexity that; exhaustive searching benchmark; interactive multiview video streaming; interview correlation; interview prediction structure; multiview video coding; prediction coding dependency; spatial correlation; temporal correlation; user interactive behavior model; visual distortion constraint; Encoding; Quantization (signal); Interactive Multiview Video Streaming (IMVS); Multiview Video Coding (MVC); optimal prediction structure; view popularity model;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Picture Coding Symposium (PCS), 2013
  • Conference_Location
    San Jose, CA
  • Print_ISBN
    978-1-4799-0292-7
  • Type

    conf

  • DOI
    10.1109/PCS.2013.6737710
  • Filename
    6737710