A benchmarking campaign for the multimodal detection of violent scenes in movies
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
A naive mid-level concept-based fusion approach to violence detection in Hollywood movies
Proceedings of the 3rd ACM conference on International conference on multimedia retrieval
Violent scene detection using mid-level feature
Proceedings of the Fourth Symposium on Information and Communication Technology
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As violence in movies has harmful influence on children, in this paper, we propose an algorithm to detect violent scene in movies. Under our definition of violence, the task of violent scene detection is decomposed into action scene detection and bloody frame detection. While previous approaches addressed on shot level of video structure only, our approach works on more semantic-complete scene structure of video. The input video (digital movie) is first segmented into several scenes. Based on the filmmaking characteristics of action scene, some features of the scene are extracted to feed into the support vector machine for classification. Finally, the face, blood and motion information are integrated to determine whether the action scene has violent content. Experimental results show that the proposed approach works reasonably well in detecting most of the violent scenes. Compared with related work, our approach is computationally simple yet effective.