• DocumentCode
    3244576
  • Title

    An effective framework of shot segmentation based on I-Frame in compressed-domain videos

  • Author

    Jin-Long Zheng ; Ming-Jun Li ; Ming-Xin Zhang ; Jian Zhou ; Zai-De Liu

  • Author_Institution
    Sch. of Comput. Sci. & Eng., Changshu Inst. of Technol., Changshu, China
  • fYear
    2012
  • fDate
    15-17 July 2012
  • Firstpage
    84
  • Lastpage
    90
  • Abstract
    In this paper, we propose an effective frame of shot segmentation in compress-domain videos. Firstly, we extract DC coefficients of I-frames in compressed-domain, and construct a sequence of DC-images which are on the basis of DC coefficients in I-Frames. Secondly, the difference between two adjacent DC-images is calculated by integrating grid-mapping dynamic window, color moments and spatial distribution entropy of colors. It comes true that most shot boundaries are pre-detected. Finally, more accurate shot boundaries or wrong shot boundaries are detected by the analysis of Macro-block in P or B frame between two adjacent I-Frames on a detected segmentation position. The experiments show that the frame efficiently has improved the performance of shot detection, and to a certain extent, the complexity of the shot detection can be reduced.
  • Keywords
    data compression; entropy; feature extraction; image colour analysis; image segmentation; image sequences; object detection; video coding; B frame; DC coefficients extraction; DC-images sequence; I-frame; P frame; accurate shot boundary detection; color moments; color spatial distribution entropy; compressed-domain videos; grid-mapping dynamic window; macro-block analysis; shot segmentation framework; wrong shot boundary detection; Distribution functions; Entropy; Graphical models; Image color analysis; Pattern recognition; Videos; Wavelet analysis; Color Moment; Compressed-domain; Dynamic Window; Shot Segmentation; Spatial Distribution Entropy of Colors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Analysis and Pattern Recognition (ICWAPR), 2012 International Conference on
  • Conference_Location
    Xian
  • ISSN
    2158-5695
  • Print_ISBN
    978-1-4673-1534-0
  • Type

    conf

  • DOI
    10.1109/ICWAPR.2012.6294760
  • Filename
    6294760