참고문헌
- Sultani, W., C. Chen, and M. Shah. Real-world anomaly detection in surveillance videos. in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018.
- Bilinski, P. and F. Bremond. Human violence recognition and detection in surveillance videos. in 2016 13th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS). 2016. IEEE.
- Nievas, E.B., et al. Violence detection in video using computer vision techniques. in International conference on Computer analysis of images and patterns. 2011. Springer.
- Nam, J., M. Alghoniemy, and A.H. Tewfik. Audio-visual content-based violent scene characterization. in Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No. 98CB36269). 1998. IEEE.
- Lin, J., Y. Sun, and W. Wang. Violence detection in movies with auditory and visual cues. in 2010 International Conference on Computational Intelligence and Security. 2010. IEEE.
- Zajdel, W., et al. CASSANDRA: audio-video sensor fusion for aggression detection. in 2007 IEEE conference on advanced video and signal based surveillance. 2007. IEEE.
- Sajjad, M., et al., Raspberry Pi assisted facial expression recognition framework for smart security in law-enforcement services. Information Sciences, 2019. 479: p. 416-431. https://doi.org/10.1016/j.ins.2018.07.027
- Ullah, A., et al., Action recognition in video sequences using deep bi-directional LSTM with CNN features. IEEE Access, 2017. 6: p. 1155-1166. https://doi.org/10.1109/ACCESS.2017.2778011
- Sun, L., et al. Human action recognition using in Proceedings of the IEEE international conference on computer vision. 2015.
- Ullah, F.U.M., et al., Violence detection using spatiotemporal features with 3D convolutional neural network. Sensors, 2019. 19(11): p. 2472. https://doi.org/10.3390/s19112472
- Benabbas, Y., N. Ihaddadene, and C. Djeraba, Motion pattern extraction and event detection for automatic visual surveillance. EURASIP Journal on Image and Video Processing, 2011. 2011(1): p. 163682.
- Hassner, T., Y. Itcher, and O. Kliper-Gross. Violent flows: Real-time detection of violent crowd behavior. in 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. 2012. IEEE.
- Adam, A., et al., Robust real-time unusual event detection using multiple fixed-location monitors. IEEE transactions on pattern analysis and machine intelligence, 2008. 30 (3): p. 555-560. https://doi.org/10.1109/TPAMI.2007.70825
- Blunsden, S. and R. Fisher, The BEHAVE video dataset: ground truthed video for multi-person behavior classification. Annals of the BMVA, 2010. 4(1-12): p. 4.
- Grega, M., et al., Automated detection of firearms and knives in a CCTV image. Sensors, 2016. 16(1): p. 47. https://doi.org/10.3390/s16010047
- Zhou, P., et al. Violent interaction detection in video based on deep learning. in Journal of Physics: Conference Series. 2017. IOP Publishing.
- Veenendaal, A., et al., Fight and Aggression Recognition using Depth and Motion Data. Computer Science and Emerging Research Journal, 2016. 4.
- Ravanbakhsh, M., et al. Plug-and-play cnn for crowd motion analysis: An application in abnormal event detection. in 2018 IEEE Winter Conference on Applications of Computer Vision (WACV). 2018. IEEE.
- Amin Ullah, Jamil Ahmad, Khan Muhammad, Irfan Mehmood, Mi Young Lee, Jun Ryeol Park, Sung Wook Baik. (2017). Action Recognition in Movie Scenes using Deep Features of Keyframes. THE JOURNAL OF KOREAN INSTITUTE OF NEXT GENERATION COMPUTING, 13(3), 7-14
- Fath U Min Ullah, Amin Ullah, Khan Muhammad, Mi Young Lee, Sung Wook Baik. (2018). Violence Recognition using Deep CNN for Smart Surveillance Applications. THE JOURNAL OF KOREAN INSTITUTE OF NEXT GENERATION COMPUTING, 14(5), 53-59.
- Amin Ullah, Nasir Rahim, Jamil Ahmad, Mi Young Lee, Sung Wook Baik. (2017). Analyzing Pedestrian Parts using Deep Features for Person Re-Identification. THE JOURNAL OF KOREAN INSTITUTE OF NEXT GENERATION COMPUTING, 13(2), 82-92.