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Title

Automatic Violence Scenes Detection: A Multi-Modal Approach

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Published in Working Notes Proceedings of the MediaEval 2011 Workshop. Santa Croce in Fossabanda, Pisa, Italy - September 1-2, 2011 - . 2011
Abstract In this working note, we propose a set of features and a classification scheme for detecting automatically violent scenes in movies. The features are extracted from audio, video, and subtitles modalities of the movies. In violent scenes classification, we found the following features relevant: the short time audio energy, motion component, and shot words rate.We classified the shots into violent and non-violent using naive Bayesian, Linear Discriminant Analysis (LDA), and Quadratic Discriminant Analysis (QDA) targeting to maximize the precision of the detection in the first two minutes of retrieved content.
Keywords ViolenceAudio feature extractionVisual feature extractionText-based featuresSubtitlesViolence scenes detectionClassification
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Research groups Computer Vision and Multimedia Laboratory
Multimodal Interaction Group
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GNINKOUN, Gabin, SOLEYMANI, Mohammad. Automatic Violence Scenes Detection: A Multi-Modal Approach. In: Working Notes Proceedings of the MediaEval 2011 Workshop. Santa Croce in Fossabanda, Pisa, Italy. [s.l.] : [s.n.], 2011. https://archive-ouverte.unige.ch/unige:74292

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Deposited on : 2015-07-22

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