Conference paper Open Access
A Crowd Analysis Framework for Detecting Violence Scenes
Konstantinos Gkountakos; Konstantinos Ioannidis; Theodora Tsikrika; Stefanos Vrochidis; Ioannis Kompatsiaris
This work examines violence detection in video scenes of crowds and proposes a crowd violence detection framework based on a 3D convolutional deep learning architecture, the 3D-ResNet model with 50 layers. The proposed framework is evaluated on the Violent Flows dataset against several state-of-the-art approaches and achieves higher accuracy values in almost all cases, while also performing the violence detection activities in (near) real-time.
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Indexed in
- Publication date:
- April 14, 2020
- DOI:
-
- Keyword(s):
- Violence detection Crowd analysis Deep learning 3D-convolutional neural networks Violent Flows
- Grants:
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European Commission:
- CONNEXIONs - InterCONnected NEXt-Generation Immersive IoT Platform of Crime and Terrorism DetectiON, PredictiON, InvestigatiON, and PreventiON Services (786731)
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International