• DocumentCode
    597960
  • Title

    An abstraction based reduced reference depth perception metric for 3D video

  • Author

    Nur, G. ; Akar, Gozde Bozdagi

  • Author_Institution
    Electr. & Electron. Eng. Dept., Kirikkale Univ., Krkkale, Turkey
  • fYear
    2012
  • fDate
    Sept. 30 2012-Oct. 3 2012
  • Firstpage
    625
  • Lastpage
    628
  • Abstract
    In order to speed up the wide-spread proliferation of the 3D video technologies (e.g., coding, transmission, display, etc), the effect of these technologies on 3D perception should be efficiently and reliably investigated. Using Full-Reference (FR) objective metrics for this investigation is not practical especially for “on the fly” 3D perception evaluation. Thus, a Reduced Reference (RR) metric is proposed to predict the depth perception of 3D video in this paper. The color-plus-depth 3D video representation is exploited for the proposed metric. Since the significant depth levels of the depth map sequences have great influence on the depth perception of users, they are considered as side information in the proposed RR metric. To determine the significant depth levels, the depth map sequences are abstracted using bilateral filter. Video Quality Metric (VQM) is utilized to predict the depth perception ensured by the significant depth levels due to its well correlation with the Human Visual System (HVS). The performance assessment results present that the proposed RR metric can be utilized in place of a FR metric to reliably measure the depth perception of 3D video with a low overhead.
  • Keywords
    image representation; video signal processing; visual perception; FR metric; FR objective metrics; HVS; RR metric; VQM; Video Quality Metric; abstraction-based reduced reference depth perception metric; bilateral filter; color-plus-depth 3D video representation; depth map sequences; full-reference objective metrics; human visual system; on the fly 3D perception evaluation; reduced reference metric; Information filtering; Measurement; PSNR; Quality assessment; Reliability; Video recording; Video sequences; 3D Video; Bilateral Filter; Depth Map Abstraction; Depth Perception; Reduced Reference Metric;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing (ICIP), 2012 19th IEEE International Conference on
  • Conference_Location
    Orlando, FL
  • ISSN
    1522-4880
  • Print_ISBN
    978-1-4673-2534-9
  • Electronic_ISBN
    1522-4880
  • Type

    conf

  • DOI
    10.1109/ICIP.2012.6466937
  • Filename
    6466937