Video Surveillance for Dangerous Situations in Public Spaces

• Main Authors: Nikita Bazhenov, Egor Rybin, Dmitry Korzun
• Format: Article in Journal/Newspaper
• Language: English
• Published: FRUCT 2023
• Subjects: video analytics; dangerous situations; neural networks; data analysis; computer vision technology; artificial intelligence; machine learning; Telecommunication; TK5101-6720; Republic of Karelia
• Online Access: https://doi.org/10.5281/zenodo.10426304; https://doaj.org/article/77995847901f48ceafca98f77179298d

Many multi-camera systems organize video surveillance - a process designed to visually control a certain area and / or objects. The most modern systems organize smart video surveillance - the process of collecting and subsequent analysis of incoming information using modern technologies and designed to ensure security in those places where it is necessary. At the moment, there are a large number of algorithms and methods used in video analytics systems - a technology that uses computer vision methods for automated data acquisition based on the analysis of images from video cameras in real time. Such video analytics systems are mainly used in special services. In the case of commercial and public use, they are expensive or not available. The claimed system can be quite flexibly upgraded to suit the customer’s tasks, while having a low cost. At the moment, security systems in the field of video analytics are not widely used in the Republic of Karelia (RK). Video analytics is either completely absent or presented in the form of the most primitive recognition algorithms. Ensuring the digital security of the Republic of Karelia in public places and crowded places and the development of digital security support technologies in the region are among the highest priority areas of this work.