Smart Video based Threat Analysis using CNN

Authors

  • Shubhada P. Mone   Computer Engineering Department, MMCOE, Pune, Maharashtra, India
  • Mukul Borole  Computer Engineering Department, MMCOE, Pune, Maharashtra, India
  • Devashish Shahakar  Computer Engineering Department, MMCOE, Pune, Maharashtra, India
  • Dnyanesh Mahajan  

DOI:

https://doi.org//10.32628/CSEIT217686

Keywords:

Video Surveillance, Background Subtraction, Suspicious Activity, Suspicious Object, Alert Generation, CNN.

Abstract

In recent years, more and more video surveillance devices like drones, CCTV's have been deployed due to an increase in demands related to public security and smart cities. There is a need to overcome the existing drawbacks of post-investigation techniques of video surveillance systems by providing a pre-alert generation system. The video surveillance system has become an important part of the security and protection of modern cities. So we are going to focus on video surveillance by giving video contents containing early fire events detection, suspicious activities and smart parking systems, and crowd estimation. Smart monitoring cameras equipped with intelligent video analytics techniques can monitor and pre-alert systems by capturing suspicious activity and events. Our work is based on deep learning techniques for video analysis with better performance and event detection with the advantages of alert generation.

References

  1. Tejashri Subhash Bora, Monika Dhananjay Rokade “Human suspicious activity detection system using CNN model for video surveillance”. International Journal of Advance Research and Innovative Ideas in Education
  2. C. V. Amrutha, C. Jyotsna and J. Amudha, "Deep Learning Approach for Suspicious Activity Detection from Surveillance Video," 2020 2nd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA)
  3. Vallathan, G., John, A., Thirumalai, C. et al. “Suspicious activity detection using deep learning in secure assisted living IoT environments”. J Supercomput 77, 3242–3260 (2021).
  4. Trupti M. Pandit, P.M.Jadhav, A.C.Phadke, “Suspicious Object Detection In Surveillance Videos For Security Applications”.  in 2016 International Conference on Inventive Computation Technologies (ICICT),added in IEEE Xplore 19 January 2017
  5. Rachana Gugale, Abhiruchi Shendkar, Arisha Chamadia, Swati Patra, Deepali Ahir “Human Suspicious Activity Detection using Deep Learning” in International Research Journal of Engineering and Technology (IRJET) ,Volume: 07 Issue: 06 | June 2020
  6. Patel Parin, Gayatri Pandi “ Traffic Monitoring using Video Stream with Machine Learning: Based on Big Data Process with Cloud”. International Journal of Innovations & Advancement in Computer Science 2017
  7. Jeany Son,Mooyeol Baek,Minsu Cho,Bohyung Han “Multi-Object Tracking with Quadruplet Convolutional Neural Networks” Dept. of Computer Science and Engineering, POSTECH, Korea 2017

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Published

2021-12-30

Issue

Section

Research Articles

How to Cite

[1]
Shubhada P. Mone , Mukul Borole, Devashish Shahakar, Dnyanesh Mahajan, " Smart Video based Threat Analysis using CNN, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 8, Issue 1, pp.128-130, January-February-2022. Available at doi : https://doi.org/10.32628/CSEIT217686