Nazgul Zholmagambetova
ABSTRACT
Security systems are extremely important in the workplaces, educational establishments and other public places. Nowadays, in a wide range of scenarios, such as offices, schools, universities, factories, can be detected various anomaly behaviors, which may lead to potential danger. It is extremely important, as it can help to reduce risk from both personal and property safety. Thus, the purpose of the current study is to improve security systems with deep learning techniques, as computational power and hardware itself recently have improved tremendously. Human-Machine Interaction also benefits in this case, as machines can help people analyze the environment and prevent danger in time, thus creating a safer environment. In order to recognize, distinguish and analyze people's behavior, a new approach of combination of Face Recognition with masks and Human-Action Recognition algorithm with deep learning techniques is introduced in this security system. Provided approach consists of algorithms, which are considered as SOTA at each specific domain, and trained for a customly collected dataset. As for the result, performance of the current method appeared to be fairly robust, which means it can be used in public places, such as offices, schools, etc.
- A. R. Syafeeza, M. K. Mohd Fitri Alif, Y. Nursyifaa Athirah, A. S. Jaafar, A. H. Norihan and M. S. Saleha: IoT based facial recognition door access control home security system using raspberry pi. International Journal of Power Electronics and Drive System, IJPEDS, vol. 11, No.1, pp. 417–424. (2020)Google Scholar
Cross Ref
- G. Senthilkumar, K. Gopalakrishnan, V. S. Kumar: Embedded image capturing system using raspberry pi system. International Journal of Emerging Trends & Technology in Computer Science, IJETTCS, vol. 3, No.2, pp. 213–215. (2014)Google Scholar
- Fatemeh Serpush, Mahdi Rezaei: Complex Human Action Recognition Using a Hierarchical Feature Reduction and Deep Learning-Based Method. SN Computer Science, vol. 2, pp. 94. (2021)Google Scholar
- Cheng-Bin Jin, Shengzhe Li, and Hakil Kim: Real-Time Action Detection in Video Surveillance using Sub-Action Descriptor with Multi-CNN. Journal of Institute of Control, Robotics and Systems, vol. 24, pp. 3. (2018)Google Scholar
- Suneth Ranasinghe, Fadi Al Machot, Heinrich C Mayr: A review on applications of activity recognition systems with regard to performance and evaluation. International Journal of Distributed Sensor Networks, vol. 12, pp. 8. (2016)Google Scholar
- Homepage, https://www.securityandsafetythings.com/insights/forget-cctv-smart-video-surveillanceGoogle Scholar
- Y. Kortli, M. Jridi, A. Al Falou, and M. Atri: Face Recognition Systems: A Survey. Sensors, vol. 20, No.2, pp. 342. (2020)Google Scholar
- N. Damer, J. H. Grebe, C. Chen, F. Boutros, F. Kirchbuchner and A. Kuijper: The Effect of Wearing a Mask on Face Recognition Performance: an Exploratory Study. 2020 International Conference of the Biometrics Special Interest Group, BIOSIG, pp. 1–6. (2020)Google Scholar
- Murat Taskiran, Nihan Kahraman, Cigdem Eroglu Erdem: Face recognition: Past, present and future (a review). Digital Signal Processing, vol. 106, 102809, ISSN 1051-2004 (2020)Google ScholarCross Ref
- Guangchun Cheng, Yiwen Wan, Abdullah N. Saudagar, Kamesh Namuduri, Bill P. Buckles: Advances in Human Action Recognition: A Survey. Computer Vision and Pattern Recognition, CVPR. (2015)Google Scholar
- Weinland D, Ronfard R, Boyer E: A survey of vision-based methods for action representation, segmentation and recognition. Computer vision and image understanding, vol. 115, pp. 224–241. (2011)Google Scholar
- Aggarwal J, Xia L: Human activity recognition from 3d data: a review. Pattern Recognition Letters, pp. 48–70. (2014)Google Scholar
- Akansha UA, Shailendra M, Singh N: Analytical review on video-based human activity recognition. Computing for Sustainable Global Development (INDIACom), 2016 3rd International Conference on. IEEE, pp. 3839–3844. (2016)Google Scholar
- Beddiar, D.R., Nini, B., Sabokrou, M.: Vision-based human activity recognition: a survey. Multimedia Tools and Applications, 79(41-42), 30509-30555. (2020)Google ScholarDigital Library
- S. Sen, M. Dhar and S. Banerjee: Implementation of human action recognition using image parsing techniques. Emerging Trends in Electronic Devices and Computational Techniques, EDCT, pp. 1–6. (2018)Google Scholar
- Grigorios G. Chrysos, Stylianos Moschoglou, Giorgos Bouritsas, Yannis Panagakis, Jiankang Deng, Stefanos Zafeiriou: Deep Polynomial Neural Networks. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR, pp. 7325–7335. (2020)Google Scholar
- Homepage, https://paperswithcode.com/sota/face-recognition-on-lfwGoogle Scholar
- Homepage, http://vis-www.cs.umass.edu/lfw/Google Scholar
- Z. Cao, G. Hidalgo, T. Simon, S.-E. Wei and Y. Sheikh: OpenPose: Realtime Multi-Person 2D Pose Estimation Using Part Affinity Fields. IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.43, No.1, pp. 172-186. (2021)Google ScholarDigital Library
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