• DocumentCode
    2171085
  • Title

    Open collaboration on hybrid video quality models - VQEG joint effort group hybrid

  • Author

    Barkowsky, Marcus ; Staelens, Nicolas ; Janowski, Lucjan

  • Author_Institution
    IRCCyN, LUNAM Univ., Nantes, France
  • fYear
    2013
  • fDate
    Sept. 30 2013-Oct. 2 2013
  • Firstpage
    476
  • Lastpage
    481
  • Abstract
    Several factors limit the advances on automatizing video quality measurement. Modelling the human visual system requires multi- and interdisciplinary efforts. A joint effort may bridge the large gap between the knowledge required in conducting a psychophysical experiment on isolated visual stimuli to engineering a universal model for video quality estimation under real-time constraints. The verification and validation requires input reaching from professional content production to innovative machine learning algorithms. Our paper aims at highlighting the complex interactions and the multitude of open questions as well as industrial requirements that led to the creation of the Joint Effort Group in the Video Quality Experts Group. The paper will zoom in on the first activity, the creation of a hybrid video quality model.
  • Keywords
    learning (artificial intelligence); video coding; H.265 video coding; VQEG joint effort group hybrid; human visual system; hybrid video quality models; innovative machine learning algorithms; psychophysical experiment; video quality estimation; video quality experts group; video quality measurement; visual stimuli; Databases; Joints; Measurement; Quality assessment; Standards; Video recording; Video sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Signal Processing (MMSP), 2013 IEEE 15th International Workshop on
  • Conference_Location
    Pula
  • Type

    conf

  • DOI
    10.1109/MMSP.2013.6659335
  • Filename
    6659335