• DocumentCode
    1396725
  • Title

    Mixed ranking scheme for video retrieval

  • Author

    Feng, Y. ; Ren, Jinchang ; Jiang, Jianliang

  • Author_Institution
    Sch. of Inf., Univ. of Bradford, Bradford, UK
  • Volume
    46
  • Issue
    24
  • fYear
    2010
  • Firstpage
    1600
  • Lastpage
    1601
  • Abstract
    A unified ranking scheme for effective video retrieval is proposed, in which low-level visual feature terms and high-level image category features are combined organically to inspire effective retrieval in the manner of semantics. By taking these features as a joint fact of document relevance, the BM25 model, popular in text retrieval, is employed to determine a mixed similarity rank of video documents. Experiments using the well-known TRECVID retrieval dataset have validated the superiority of the methodology.
  • Keywords
    content-based retrieval; feature extraction; video retrieval; BM25 model; TRECVID retrieval dataset; document relevance; image category features; mixed ranking scheme; video document ranking; video retrieval; visual feature terms;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el.2010.8621
  • Filename
    5659664
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1396725