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Original Article
Real-Time Crowd Crime and Violence Detection Using Deep Learning-Based Face Recognition and Object Detection
Kehkeshan Fatima1
Dr. Mohd Rafi Ahmed2
1Student, MCA, Deccan College of Engineering and Technology, Hyderabad, Telangana, India. 2Associate Professor, MCA, Deccan College of Engineering and Technology, Hyderabad, Telangana, India.
Published Online: July-August 2025
Pages: 20-23
Cite this article
↗ https://www.doi.org/10.59256/ijsreat.20250504004
References
1. J. Redmon and A. Farhadi, “YOLOv3: An Incremental Improvement,” arXiv preprint arXiv:1804.02767, 2018.
2. A. Bochkovskiy, C.-Y. Wang, and H.-Y. M. Liao, “YOLOv4: Optimal Speed and Accuracy of Object Detection,” arXiv preprint arXiv:2004.10934, 2020.
3. K. He, X. Zhang, S. Ren, and J. Sun, “Deep Residual Learning for Image Recognition,” in Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2016.
4. O. M. Parkhi, A. Vedaldi, and A. Zisserman, “Deep Face Recognition,” in Proc. of the British Machine Vision Conference (BMVC), 2015.
5. OpenCV, “Open Source Computer Vision Library,” [Online]. Available: https://opencv.org/, 2023.
6. PyTorch, “An Open Source Machine Learning Framework,” [Online]. Available: https://pytorch.org/, 2023.
7. TensorFlow, “An End-to-End Open Source Machine Learning Platform,” [Online]. Available: https://www.tensorflow.org/, 2023.
8. Streamlit, “The Fastest Way to Build and Share Data Apps,” [Online]. Available: https://streamlit.io/, 2023.
9. F. Ahmed et al., “Real-Time Video Surveillance with YOLO for Crime Detection,” International Journal of Computer Applications, vol. 183, no. 46, pp. 32–37, 2022.
10. D. Zhang et al., “Smart Surveillance: A Deep Learning Approach for Real-Time Violence Detection,” IEEE Transactions on Multimedia, vol. 23, pp. 3556–3566, 2021.
11. R. Chowdhury et al., “Real-Time Action Recognition Using Two-Stream CNNs,” in Proc. of the IEEE Conf. on CVPR Workshops, 2018.
12. T. Hassner, S. Harel, E. Paz, and R. Enbar, “Effective Face Frontalization in Unconstrained Images,” in Proc. of the IEEE Conf. on CVPR, 2015.
13. M. S. Ali, A. Shah, and H. Khan, “AI-Driven Smart City Surveillance: Techniques and Applications,” Smart Cities, vol. 4, no. 1, pp. 15–30, 2021.
14. P. Viola and M. J. Jones, “Robust Real-Time Face Detection,” International Journal of Computer Vision, vol. 57, no. 2, pp. 137–154, 2004.
15. S. Razavian, H. Azizpour, J. Sullivan, and S. Carlsson, “CNN Features Off-the-Shelf: An Astounding Baseline for Recognition,” in Proc. of the IEEE Conf. on CVPR Workshops, 2014.
2. A. Bochkovskiy, C.-Y. Wang, and H.-Y. M. Liao, “YOLOv4: Optimal Speed and Accuracy of Object Detection,” arXiv preprint arXiv:2004.10934, 2020.
3. K. He, X. Zhang, S. Ren, and J. Sun, “Deep Residual Learning for Image Recognition,” in Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2016.
4. O. M. Parkhi, A. Vedaldi, and A. Zisserman, “Deep Face Recognition,” in Proc. of the British Machine Vision Conference (BMVC), 2015.
5. OpenCV, “Open Source Computer Vision Library,” [Online]. Available: https://opencv.org/, 2023.
6. PyTorch, “An Open Source Machine Learning Framework,” [Online]. Available: https://pytorch.org/, 2023.
7. TensorFlow, “An End-to-End Open Source Machine Learning Platform,” [Online]. Available: https://www.tensorflow.org/, 2023.
8. Streamlit, “The Fastest Way to Build and Share Data Apps,” [Online]. Available: https://streamlit.io/, 2023.
9. F. Ahmed et al., “Real-Time Video Surveillance with YOLO for Crime Detection,” International Journal of Computer Applications, vol. 183, no. 46, pp. 32–37, 2022.
10. D. Zhang et al., “Smart Surveillance: A Deep Learning Approach for Real-Time Violence Detection,” IEEE Transactions on Multimedia, vol. 23, pp. 3556–3566, 2021.
11. R. Chowdhury et al., “Real-Time Action Recognition Using Two-Stream CNNs,” in Proc. of the IEEE Conf. on CVPR Workshops, 2018.
12. T. Hassner, S. Harel, E. Paz, and R. Enbar, “Effective Face Frontalization in Unconstrained Images,” in Proc. of the IEEE Conf. on CVPR, 2015.
13. M. S. Ali, A. Shah, and H. Khan, “AI-Driven Smart City Surveillance: Techniques and Applications,” Smart Cities, vol. 4, no. 1, pp. 15–30, 2021.
14. P. Viola and M. J. Jones, “Robust Real-Time Face Detection,” International Journal of Computer Vision, vol. 57, no. 2, pp. 137–154, 2004.
15. S. Razavian, H. Azizpour, J. Sullivan, and S. Carlsson, “CNN Features Off-the-Shelf: An Astounding Baseline for Recognition,” in Proc. of the IEEE Conf. on CVPR Workshops, 2014.
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