Abstract
This project aims to deliver a system which detects violence in the crowd. The model does not need human intervention to detect violence as it is automated. A dataset has been collected for detecting whether violence is taking place or not. The dataset includes both the scenarios, the ones which contain violence and ones which does not. Then, the model is trained to analyze whether the scenario contains violence or not. To detect scenarios which contain violent instances, various deep learning algorithms are applied on the dataset. CNN and LSTM-based architectures are experimented separately and in combination on this dataset. The model can be easily implemented in CCTV camera systems because it is lightweight.
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Deshmukh, A., Warang, K., Pente, Y., Marathe, N. (2021). Violence Detection Through Surveillance System. In: Tuba, M., Akashe, S., Joshi, A. (eds) ICT Systems and Sustainability. Advances in Intelligent Systems and Computing, vol 1270. Springer, Singapore. https://doi.org/10.1007/978-981-15-8289-9_49
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DOI: https://doi.org/10.1007/978-981-15-8289-9_49
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