• DocumentCode
    1740397
  • Title

    A high-level semantics extraction model for stored videos

  • Author

    Liu, Yan ; Li, Fei

  • Author_Institution
    Dept. of Comput. Sci., Hong Kong Univ. of Sci. & Technol., Kowloon, China
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    71
  • Lastpage
    74
  • Abstract
    Digital video databases have become more pervasive, and finding video clips in video databases is quickly becoming a major bottleneck. Indexing and annotation can help video systems retrieve appropriate video clips fast. Currently, these techniques are based on computation on image low-level features and manual annotation, whose low success ratio and retrieval speed limit the applications of video databases. In this paper, we consider the semantic interpretation of the the contents as a form of annotation for video clips. We give a self-adaptive high-level description model for application-oriented semantics extraction, which annotates and retrieves video clips flexibly and automatically
  • Keywords
    content-based retrieval; database indexing; video databases; annotation; application-oriented semantics extraction; digital video databases; high-level semantics extraction model; image low-level features; indexing; self-adaptive high-level description model; stored videos; video clip retrieval; Computer science; Content based retrieval; Data mining; Feature extraction; Image retrieval; Information retrieval; Layout; Prototypes; Spatial databases; Videos;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia Software Engineering, 2000. Proceedings. International Symposium on
  • Conference_Location
    Taipei
  • Print_ISBN
    0-7695-0933-9
  • Type

    conf

  • DOI
    10.1109/MMSE.2000.897194
  • Filename
    897194