• DocumentCode
    2576676
  • Title

    Effective and efficient sports highlights extraction using the minimum description length criterion in selecting GMM structures [audio classification]

  • Author

    Xiong, Ziyou ; Radhakrishnan, Rathnakumar ; Divakaran, Ajay ; Huang, Thomas S.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Illinois Univ., Urbana, IL, USA
  • Volume
    3
  • fYear
    2004
  • fDate
    27-30 June 2004
  • Firstpage
    1947
  • Abstract
    In fitting the training data with Gaussian mixture models (GMMs) of appropriate structures using the MDL (minimum description length) criterion, we are able to improve audio classification accuracy with a large margin. With the MDL-GMMs, we are also able to greatly improve the accuracy in extracting sports highlights. Since we have focused on audio domain processing, it enables us to extract highlights very quickly. We have demonstrated the importance of a better understanding of model structures in such a pattern recognition task.
  • Keywords
    Gaussian distribution; audio signal processing; classification; feature extraction; multimedia computing; GMM structures; Gaussian mixture models; MDL-GMM; audio classification accuracy; audio domain processing; minimum description length estimator; pattern recognition; sports highlights extraction; training data fitting; video analysis; Clustering algorithms; Data engineering; Data mining; Electronic mail; Feature extraction; Laboratories; Maximum likelihood estimation; Parameter estimation; Pattern recognition; Training data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo, 2004. ICME '04. 2004 IEEE International Conference on
  • Print_ISBN
    0-7803-8603-5
  • Type

    conf

  • DOI
    10.1109/ICME.2004.1394642
  • Filename
    1394642