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- W1488805901 abstract "In this paper we introduce stochastic models that characterize the structure of typical television program genres. We show how video sequences can be represented using discrete-symbol sequences derived from shot features. We then use these sequences to build HMM and hybrid HMM-SCFG models which are used to automatically classify the sequences into genres. In contrast to previous methods for using SCGFs for video processing, we use unsupervised training without an a priori grammar." @default.
- W1488805901 created "2016-06-24" @default.
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- W1488805901 date "2003-01-01" @default.
- W1488805901 modified "2023-09-23" @default.
- W1488805901 title "Stochastic Models of Video Structure for Program Genre Detection" @default.
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- W1488805901 doi "https://doi.org/10.1007/978-3-540-39798-4_13" @default.
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