• DocumentCode
    1708222
  • Title

    Video segmentation and key frame extraction with parametric model

  • Author

    Chen, Wei ; Zhang, Yu-Jin

  • Author_Institution
    Dept. of Electron. Eng., Tsinghua Univ., Beijing
  • fYear
    2008
  • Firstpage
    1020
  • Lastpage
    1023
  • Abstract
    In this paper, a parametric model for video segmentation and key frame extraction in the video content analysis is proposed. The autoregressive (AR) modeling is used to model the feature sequence of frames over time and to make the future content analysis in the AR parametric space. Based on this parametric framework, detecting shot boundaries in video sequences and extracting key frames from shots are conducted. Real experiments results are presented to illustrate the good performance of this new method.
  • Keywords
    autoregressive processes; feature extraction; image sequences; video signal processing; autoregressive modeling; key frame extraction; parametric model; video content analysis; video segmentation; video sequences; Cameras; Gunshot detection systems; Learning systems; Object detection; Parameter estimation; Parametric statistics; Predictive models; Resonance light scattering; Video sequences; White noise; Autoregressive model; Key frame extraction; Video content analysis; Video segmentation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, Control and Signal Processing, 2008. ISCCSP 2008. 3rd International Symposium on
  • Conference_Location
    St Julians
  • Print_ISBN
    978-1-4244-1687-5
  • Electronic_ISBN
    978-1-4244-1688-2
  • Type

    conf

  • DOI
    10.1109/ISCCSP.2008.4537373
  • Filename
    4537373