Content-Based Video Classification Using Support Vector Machines

  • Vakkalanka Suresh
  • C. Krishna Mohan
  • R. Kumara Swamy
  • B. Yegnanarayana
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3316)

Abstract

In this paper, we investigate the problem of video classification into predefined genre. The approach adopted is based on spatial and temporal descriptors derived from short video sequences (20 seconds). By using support vector machines (SVMs), we propose an optimized multi-class classification method. Five popular TV broadcast genre namely cartoon, commercials, cricket, football and tennis are studied. We tested our scheme on more than 2 hours of video data and achieved an accuracy of 92.5%.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Vakkalanka Suresh
    • 1
  • C. Krishna Mohan
    • 1
  • R. Kumara Swamy
    • 1
  • B. Yegnanarayana
    • 1
  1. 1.Speech and Vision Laboratory, Department of Computer Science and EngineeringIndian Institute of Technology MadrasChennaiIndia

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