Automatic rating of movies using an arousal curve extracted from video features
This paper discusses the extraction of film structure features from action films to build an arousal curve. The arousal curve is used as training data for building a Hidden Markov Model for predicting the rating of a movie. Evaluation of the model resulted in a 70% accuracy, which shows that there i...
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| Main Authors: | , , |
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| Format: | text |
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Animo Repository
2014
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/1858 https://animorepository.dlsu.edu.ph/context/faculty_research/article/2857/type/native/viewcontent/HNICEM.2014.7016211 |
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| Institution: | De La Salle University |
| Summary: | This paper discusses the extraction of film structure features from action films to build an arousal curve. The arousal curve is used as training data for building a Hidden Markov Model for predicting the rating of a movie. Evaluation of the model resulted in a 70% accuracy, which shows that there is some form of correlation between the structure of a film and its perceived rating. Interesting similarities were also observed in the arousal curve patterns between different movies in the same classifications. © 2014 IEEE. |
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