• DocumentCode
    1816263
  • Title

    Using multiclass SVM and MP for audio recognition of action scenes

  • Author

    Xiaohui, Wang ; FengJuan, Guo

  • Author_Institution
    Sch. of Comput. Sci. & Technol., North China Electr. Power Univ., Baoding, China
  • fYear
    2010
  • fDate
    19-20 June 2010
  • Firstpage
    273
  • Lastpage
    276
  • Abstract
    The paper presents a system for sounds classification of action scenes. We propose to use the matching pursuit (MP) algorithm to obtain effective time-frequency features. The MP-based method utilizes a dictionary of atoms for feature selection, resulting in a flexible, intuitive and physically interpretable set of features. Then apply multiclass support vector machine based on improved binary tree algorithm to classify the sounds. The paper considers six type sounds: the sword sound, the club sound, the unarmed sound, the broken sound, the metal-falling sound and the shout sound. Experimental results prove that the method is effective.
  • Keywords
    audio signal processing; pattern classification; support vector machines; trees (mathematics); action scenes; audio recognition; binary tree; feature selection; matching pursuit; multiclass SVM; multiclass support vector machine; sounds classification; time-frequency features; Classification algorithms; Gabor atom; audio feature; binary tree; matching pursuit; multiclass SVM;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Energy Engineering (ICAEE), 2010 International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-7831-6
  • Type

    conf

  • DOI
    10.1109/ICAEE.2010.5557564
  • Filename
    5557564