• DocumentCode
    514699
  • Title

    Key Frame Extraction Based on Connectivity Clustering

  • Author

    Xiao, Yongliang ; Xia, Limin

  • Author_Institution
    Sch. of Inf. Sci. & Eng., Central South Univ., Changsha, China
  • Volume
    1
  • fYear
    2010
  • fDate
    6-7 March 2010
  • Firstpage
    174
  • Lastpage
    177
  • Abstract
    Key frames play a very important role in video retrieval. In this paper, we introduce a novel method to extract key frames to represent video shot based on connectivity clustering. Compared with other methods, the proposed method can dynamically divide the frames into clusters depending on the content of shot, and then the frame closest to the cluster centroid is chosen as the key frame for the video shot. Experimental results and the comparisons with other methods on various types of video sequences illustrate the high performance of the proposed method.
  • Keywords
    image sequences; pattern clustering; video retrieval; connectivity clustering; key frame extraction; video retrieval; video shot; Clustering algorithms; Computer science; Computer science education; Data mining; Educational technology; Information management; Information retrieval; Information science; Pattern recognition; Video sequences; connectivity clustering; key frame; shot; video retrieval;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Education Technology and Computer Science (ETCS), 2010 Second International Workshop on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-6388-6
  • Electronic_ISBN
    978-1-4244-6389-3
  • Type

    conf

  • DOI
    10.1109/ETCS.2010.129
  • Filename
    5458784