• DocumentCode
    3203661
  • Title

    Are Concept Detector Lexicons Effective for Video Search?

  • Author

    Snoek, Cees G M ; Worring, Marcel

  • Author_Institution
    Univ. of Amsterdam, Amsterdam
  • fYear
    2007
  • fDate
    2-5 July 2007
  • Firstpage
    1966
  • Lastpage
    1969
  • Abstract
    Until now, systematic studies on the effectiveness of concept detectors for video search have been carried out using less than 20 detectors, or in combination with other retrieval techniques. We investigate whether video search using just large concept detector lexicons is a viable alternative for present day approaches. We demonstrate that increasing the number of concept detectors in a lexicon yields improved video retrieval performance indeed. In addition, we show that combining concept detectors at query time has the potential to boost performance further. We obtain the experimental evidence on the automatic video search task of TRECVID 2005 using 363 machine learned concept detectors.
  • Keywords
    video retrieval; TRECVID 2005; automatic video search task; concept detector lexicons; retrieval techniques; video retrieval performance; Benchmark testing; Detectors; Helicopters; Indexing; Information retrieval; Intelligent systems; Prototypes; Search engines; Speech; Streaming media;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo, 2007 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    1-4244-1016-9
  • Electronic_ISBN
    1-4244-1017-7
  • Type

    conf

  • DOI
    10.1109/ICME.2007.4285063
  • Filename
    4285063