Abstract
In this paper we present a method for the detection of violent movies in video sharing sites. The proposed method operates on three modalities: text, video and audio, the former being collected from the accompanying synopsis and user comments. Towards our goal, a multi-step approach is followed: initially, the text information is utilized to build a pre-classifier which selects the potential violent movie segments. At a second stage, a classifier is adopted, which combines the visual and audio information, in order to classify the potential violent movie segments as “violent” or “non-violent”. The experimental results on 220 movie segments from YouKu and TuDou show the effectiveness of our method.
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Zou, X., Wu, O., Wang, Q., Hu, W., Yang, J. (2013). Multi-modal Based Violent Movies Detection in Video Sharing Sites. In: Yang, J., Fang, F., Sun, C. (eds) Intelligent Science and Intelligent Data Engineering. IScIDE 2012. Lecture Notes in Computer Science, vol 7751. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36669-7_43
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DOI: https://doi.org/10.1007/978-3-642-36669-7_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-36668-0
Online ISBN: 978-3-642-36669-7
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