• DocumentCode
    595093
  • Title

    Key frame selection based on Jensen-Rényi divergence

  • Author

    Qing Xu ; Xiu Li ; Zhen Yang ; Jie Wang ; Sbert, Mateu ; Jianfu Li

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Tianjin Univ., Tianjin, China
  • fYear
    2012
  • fDate
    11-15 Nov. 2012
  • Firstpage
    1892
  • Lastpage
    1895
  • Abstract
    The key frame extraction is designed for obtaining a (very) compressed set of video frames that summarizes the essential content of a video sequence. In this paper, a well-known information theoretic measure, the Jensen-Rényi divergence (JRD), is studied to estimate the frame-by-frame distance between consecutive video images, for segmenting shots/subshots and for choosing key frames. Our new key frame extraction method, which is effective and computationally fast, contributes to a good and quick understanding of a large amount of video data.
  • Keywords
    data compression; feature extraction; image segmentation; image sequences; video coding; JRD; Jensen-Rényi divergence; content summarization; frame-by-frame distance; information theoretic measure; key frame extraction; key frame selection; subshot segmentation; video frame compressed set; video images; video sequence; Cameras; Educational institutions; Entropy; Information theory; Measurement; Pattern recognition; Video sequences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2012 21st International Conference on
  • Conference_Location
    Tsukuba
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4673-2216-4
  • Type

    conf

  • Filename
    6460524