Mass Security Surveillance Model Using Multiple CCTV
- DOI
- 10.2991/978-94-6463-529-4_10How to use a DOI?
- Keywords
- Multiple Camera; CCTV; Security; Social Network
- Abstract
In the Modern world the most important thing existing is privacy and security. Due to lack of security, people face lot of problems. In an organization it is necessary to maintain complete security from external entities. By using face recognition, the people can be authenticated, categorized and further authenticated according to their identity. To identify and allow access to the people a software based on python is used to recognize and classify the entities into known and unknown and label them in the database. And to simplify the processing of visitors and to provide access, their face data is stored in the data base which provides entry only at the specific time. The same software is used to monitor the entire premises for unknown entities all the time using distributed systems and all the face data stored in the database. If any such entity is identified without authorization in the premises, then immediately it notifies the authority.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - A. Mohan Vamsi AU - V. D. Ambeth Kumar AU - C. S. Manigandaa AU - Challapalli Manikantaa AU - P. Sindhu AU - Mayanglambam Sushilata Devi AU - V. D. Ashok Kumar PY - 2024 DA - 2024/10/04 TI - Mass Security Surveillance Model Using Multiple CCTV BT - Proceedings of the International Conference on Signal Processing and Computer Vision (SIPCOV-2023) PB - Atlantis Press SP - 97 EP - 107 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-529-4_10 DO - 10.2991/978-94-6463-529-4_10 ID - Vamsi2024 ER -