The Journal of the Acoustical Society of Korea

The Acoustical Society of Korea (한국음향학회)
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Classification of TV Program Scenes Based on Audio Information

  • Lee, Kang-Kyu (Division of Information and Computer Science, Dankook University) ;
  • Yoon, Won-Jung (Division of Information and Computer Science, Dankook University) ;
  • Park, Kyu-Sik (Division of Information and Computer Science, Dankook University)
  • Published : 2004.09.01
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Abstract

In this paper, we propose a classification system of TV program scenes based on audio information. The system classifies the video scene into six categories of commercials, basketball games, football games, news reports, weather forecasts and music videos. Two type of audio feature set are extracted from each audio frame-timbral features and coefficient domain features which result in 58-dimensional feature vector. In order to reduce the computational complexity of the system, 58-dimensional feature set is further optimized to yield l0-dimensional features through Sequential Forward Selection (SFS) method. This down-sized feature set is finally used to train and classify the given TV program scenes using κ -NN, Gaussian pattern matching algorithm. The classification result of 91.6% reported here shows the promising performance of the video scene classification based on the audio information. Finally, the system stability problem corresponding to different query length is investigated.

Keywords

References

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