Abstract
In this paper we present our research towards the detection of violent scenes in movies, employing fusion methodologies, based on learning. Towards this goal, a multi-step approach is followed: initially, automated auditory and visual processing and analysis is performed in order to estimate probabilistic measures regarding particular audio and visual related classes. At a second stage, a meta-classification architecture is adopted, which combines the audio and visual information, in order to classify mid-term video segments as "violent" or "non-violent". The proposed scheme has been evaluated on a real dataset from 10 films. © Springer-Verlag Berlin Heidelberg 2010.
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Giannakopoulos, T., Makris, A., Kosmopoulos, D., Perantonis, S., & Theodoridis, S. (2010). Audio-visual fusion for detecting violent scenes in videos. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6040 LNAI, pp. 91–100). https://doi.org/10.1007/978-3-642-12842-4_13
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