Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval
ECML '98 Proceedings of the 10th European Conference on Machine Learning
Learning and Recognizing Human Dynamics in Video Sequences
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Recognizing Action at a Distance
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Semantic context detection based on hierarchical audio models
MIR '03 Proceedings of the 5th ACM SIGMM international workshop on Multimedia information retrieval
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
International Journal of Computer Vision
Detecting Violent Scenes in Movies by Auditory and Visual Cues
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
CASSANDRA: audio-video sensor fusion for aggression detection
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
Weakly-Supervised Violence Detection in Movies with Audio and Video Based Co-training
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Violence content classification using audio features
SETN'06 Proceedings of the 4th Helenic conference on Advances in Artificial Intelligence
Audio-Visual fusion for detecting violent scenes in videos
SETN'10 Proceedings of the 6th Hellenic conference on Artificial Intelligence: theories, models and applications
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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Whereas the action recognition community has focused mostly on detecting simple actions like clapping, walking or jogging, the detection of fights or in general aggressive behaviors has been comparatively less studied. Such capability may be extremely useful in some video surveillance scenarios like in prisons, psychiatric or elderly centers or even in camera phones. After an analysis of previous approaches we test the well-known Bag-of-Words framework used for action recognition in the specific problem of fight detection, along with two of the best action descriptors currently available: STIP and MoSIFT. For the purpose of evaluation and to foster research on violence detection in video we introduce a new video database containing 1000 sequences divided in two groups: fights and non-fights. Experiments on this database and another one with fights from action movies show that fights can be detected with near 90% accuracy.