• DocumentCode
    1135015
  • Title

    Adaptive group-of-pictures and scene change detection methods based on existing H.264 advanced video coding information

  • Author

    Ding, J.-R. ; Yang, J.-F.

  • Author_Institution
    Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan
  • Volume
    2
  • Issue
    2
  • fYear
    2008
  • fDate
    4/1/2008 12:00:00 AM
  • Firstpage
    85
  • Lastpage
    94
  • Abstract
    The H.264 advanced video coding (H.264/AVC) standard provides several advanced features such as improved coding efficiency and error robustness for video storage and transmission. In order to improve the coding performance of H.264/AVC, coding control parameters such as group-of-pictures (GOP) sizes should be adaptively adjusted according to different video content variations (VCVs), which can be extracted from temporal deviation between two consecutive frames. The authors present a simple VCV estimation to design adaptive GOP detection (AGD) and scene change detection (SCD) methods by using the obtained motion information, where the motion vectors and the sum of absolute transformed differences as VCV features are effectively used to design the AGD and SCD algorithms, respectively. In order to avoid unnecessary computation, the above VCV features are obtained only in the 4times4 inter-frame prediction mode. Simulation results show that the proposed AGD with SCD methods can increase the peak signal-to-noise ratio by 0.62 dB on average over the H.264/AVC operated with a fixed GOP size. Besides, the proposed SCD method can reach a scene change detection rate of 98%.
  • Keywords
    feature extraction; motion estimation; video coding; H.264 advanced video coding; adaptive GOP detection; adaptive group-of-picture; feature extraction; motion estimation; motion vector; scene change detection method; video content variation; video storage/transmission;
  • fLanguage
    English
  • Journal_Title
    Image Processing, IET
  • Publisher
    iet
  • ISSN
    1751-9659
  • Type

    jour

  • DOI
    10.1049/iet-ipr:20070014
  • Filename
    4492752