Automatic Violence Scenes Detection: A Multi-Modal Approach

Conférence Chapitre d'actes Automatic Violence Scenes Detection: A Multi-Modal Approach eng 2011 author Gninkoun Gabin 642771 author Soleymani Mohammad 652193 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. Violence Audio feature extraction Visual feature extraction Text-based features Subtitles Violence scenes detection Classification Dewey 025.063 13 Centre universitaire d'informatique 0D3 32 Département d'informatique 18 false 895 Computer Vision and Multimedia Laboratory 725 Multimodal Interaction Group Working Notes Proceedings of the MediaEval 2011 Workshop September 1-2, 2011 Santa Croce in Fossabanda, Pisa, Italy 867bc2dd-3e47-4f29-a781-39263b0cf24a Proceedings chapter (Accepted version) Public Automatic Violence Scenes Detection_ A Multi-Modal Approach.pdf 147133 application/pdf openAccess Centres et instituts / Centre universitaire d'informatique Faculté des sciences / Département d'informatique

Title	Published in	Access level	OA Policy	Year	Views	Downloads

Automatic Violence Scenes Detection: A Multi-Modal Approach	Working Notes Proceedings of the MediaEval 2011 Workshop			2011	1,191	266

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Gninkoun, Gabin