Classification of Tv Programs Based on Audio Information Using Hidden Markov Model
نویسندگان
چکیده
This paper describes a technique for classifying TV broadcast video using Hidden Markov Model (HMM) [1]. Here we consider the problem of discriminating five types of TV programs, namely commercials, basketball games, football games, news reports, and weather forecasts. Eight frame-based audio features are used to characterize the low-level audio properties, and fourteen clip-based audio features are extracted based on these frame-based features to characterize the high-level audio properties. For each type of these five TV programs, we build an ergodic HMM using the clip-based features as observation vectors. The maximum likelihood method is then used for classifying testing data using the trained models.
منابع مشابه
Classification TV programs based on audio information using hidden Markov model
This paper describes a technique for classifying TV broadcast video using Hidden Markov Model (HMM) [1]. Here we consider the problem of discriminating five types of TV programs, namely commercials, basketball games, football games, news reports, and weather forecasts. Eight frame-based audio features are used to characterize the low-level audio properties, and fourteen clip-based audio feature...
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