Automatic Video Classification: A Survey of the Literature

  • Authors:
  • D. Brezeale;D. J. Cook

  • Affiliations:
  • Univ. of Texas, Arlington;-

  • Venue:
  • IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
  • Year:
  • 2008

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Abstract

There is much video available today. To help viewers find video of interest, work has begun on methods of automatic video classification. In this paper, we survey the video classification literature. We find that features are drawn from three modalities - text, audio, and visual - and that a large variety of combinations of features and classification have been explored. We describe the general features chosen and summarize the research in this area. We conclude with ideas for further research.