• DocumentCode
    1809772
  • Title

    A Novel Video Shot Segmentation Based on Textural Features

  • Author

    Wang, Yin ; Wen, Xiangming ; Lin, Xinqi ; He, Peizhou ; Zheng, Wei

  • Author_Institution
    Sch. of Inf. & Commun., Beijing Univ. of Posts & Telecommun., Beijing, China
  • Volume
    1
  • fYear
    2009
  • fDate
    18-20 Aug. 2009
  • Firstpage
    119
  • Lastpage
    122
  • Abstract
    In this paper, a new method for detecting shot boundaries in video sequences using box-counting to extract texture feature and judging the shot boundaries by an improve method to get a dynamic threshold is proposed. Many techniques have been developed to detect the video shot boundaries. But automatic shot boundary detection is difficult. In particular, gradual transitions are generally more difficult to detect. So the paper use the box-counting method to extract the texture feature. Then the paper use the improve method to get the dynamic threshold to detect the shot boundaries. The dynamic threshold is the average frame difference in a slide window multiplied by a threshold coefficient. Experimental results successfully validate the paper method and show that it can effectively detect both the cuts and gradual transition. In particular, the performance is better than others method when the gradual transition shot boundaries are detected.
  • Keywords
    edge detection; feature extraction; image segmentation; image sequences; image texture; object detection; video signal processing; automatic video shot boundary detection; average frame difference; box-counting method; cut detection; dynamic threshold coefficient method; gradual transition detection; slide window; textural feature extraction; video sequence; video shot segmentation; Cameras; Data mining; Feature extraction; Gunshot detection systems; Indexing; Information security; Motion detection; Object detection; Video sequences; Videoconference;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Assurance and Security, 2009. IAS '09. Fifth International Conference on
  • Conference_Location
    Xian
  • Print_ISBN
    978-0-7695-3744-3
  • Type

    conf

  • DOI
    10.1109/IAS.2009.232
  • Filename
    5283500