• DocumentCode
    2569548
  • Title

    Automatic detection of Flash movie genre using Bayesian approach

  • Author

    Ding, Dawei ; Yang, Jun ; Li, Qing ; Wang, Liping ; Wenyin, Liu

  • Author_Institution
    Dept. of Comput. Eng. & Inf. Technol., City Univ. of Hong Kong
  • Volume
    1
  • fYear
    2004
  • fDate
    30-30 June 2004
  • Firstpage
    603
  • Abstract
    As Flash, a relatively new rich media format, becomes more and more popular on the Web, the genre becomes increasingly important for Flash movie management as a complement to topical principles of classification. Genre classification can identify Flash movies authored in a style most likely to satisfy a user´s information need. We present a method for detecting the Flash genre quickly and easily by employing a Bayesian approach. A feature set for representing genre information is proposed and used to build automatic genre classification algorithms. The performance of the proposed approach is evaluated by training a Bayesian classifier on real-world data sets. Classification results from our experiments on thousands of Flash movies demonstrate the usefulness of this approach
  • Keywords
    Bayes methods; image classification; multimedia computing; Bayesian classifier; Web; automatic Flash movie detection; feature set; genre classification; movie management; rich media format; Bayesian methods; Computer science; Content based retrieval; Fires; Information technology; Internet; Motion pictures; Statistics; Technology management; Web pages;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo, 2004. ICME '04. 2004 IEEE International Conference on
  • Conference_Location
    Taipei
  • Print_ISBN
    0-7803-8603-5
  • Type

    conf

  • DOI
    10.1109/ICME.2004.1394264
  • Filename
    1394264