Abstract
To detect violence in movies, we present a three-stage method integrating visual and auditory cues. In our method, those shots with potential violent content are first identified according to universal film-making rules. A modified semi-supervised learning technique based on semi-supervised cross feature learning (SCFL) is exploited, since it is capable to combine different types of features and use unlabeled data to improve the classification performance. Then, typical violence-related audio effects are further detected for the candidate shots, and we manage to transform the confidences outputted by the classifiers of various audio events into a shot-based violence score. Finally, the first two-stage probabilistic outputs are integrated in a boosting way to generate the final inference. The experimental results on four typical action movies preliminarily show the effectiveness of our method.
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© 2008 Springer-Verlag Berlin Heidelberg
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Gong, Y., Wang, W., Jiang, S., Huang, Q., Gao, W. (2008). Detecting Violent Scenes in Movies by Auditory and Visual Cues. In: Huang, YM.R., et al. Advances in Multimedia Information Processing - PCM 2008. PCM 2008. Lecture Notes in Computer Science, vol 5353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89796-5_33
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DOI: https://doi.org/10.1007/978-3-540-89796-5_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-89795-8
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