Video Surveillance for Dangerous Situations in Public Spaces

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...

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Main Authors: Nikita Bazhenov, Egor Rybin, Dmitry Korzun
Format: Article
Language:English
Published: FRUCT 2023-11-01
Series:Proceedings of the XXth Conference of Open Innovations Association FRUCT
Subjects:
Online Access:https://www.fruct.org/publications/volume-34/acm34/files/Baz2.pdf
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author Nikita Bazhenov
Egor Rybin
Dmitry Korzun
author_facet Nikita Bazhenov
Egor Rybin
Dmitry Korzun
author_sort Nikita Bazhenov
collection DOAJ
description 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.
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spelling doaj.art-77995847901f48ceafca98f77179298d2024-01-15T12:32:23ZengFRUCTProceedings of the XXth Conference of Open Innovations Association FRUCT2305-72542343-07372023-11-01342209https://youtu.be/SKCvy_vVKOo10.5281/zenodo.10426304Video Surveillance for Dangerous Situations in Public SpacesNikita Bazhenov0Egor Rybin1Dmitry Korzun2Petrozavodsk State UniversityPetrozavodsk State UniversityPetrozavodsk State UniversityMany 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.https://www.fruct.org/publications/volume-34/acm34/files/Baz2.pdfvideo analyticsdangerous situationsneural networksdata analysiscomputer vision technologyartificial intelligencemachine learning
spellingShingle Nikita Bazhenov
Egor Rybin
Dmitry Korzun
Video Surveillance for Dangerous Situations in Public Spaces
Proceedings of the XXth Conference of Open Innovations Association FRUCT
video analytics
dangerous situations
neural networks
data analysis
computer vision technology
artificial intelligence
machine learning
title Video Surveillance for Dangerous Situations in Public Spaces
title_full Video Surveillance for Dangerous Situations in Public Spaces
title_fullStr Video Surveillance for Dangerous Situations in Public Spaces
title_full_unstemmed Video Surveillance for Dangerous Situations in Public Spaces
title_short Video Surveillance for Dangerous Situations in Public Spaces
title_sort video surveillance for dangerous situations in public spaces
topic video analytics
dangerous situations
neural networks
data analysis
computer vision technology
artificial intelligence
machine learning
url https://www.fruct.org/publications/volume-34/acm34/files/Baz2.pdf
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