scholarly journals Approaches to the Protection of Video Surveillance Systems When Applying Recognition Algorithms

2020 ◽  
Vol 14 (1) ◽  
pp. 18-22
Author(s):  
Tatiana Popova ◽  
◽  
Anatoly Afanasiev ◽  
Grigorij Zharkov ◽  
◽  
...  
Keyword(s):  
Video Surveillance ◽  
Surveillance Systems ◽  
Recognition Algorithms

scholarly journals Sistemas de reconocimiento facial, como herramienta para la búsqueda de personas

2017 ◽  
Vol 1 (8) ◽  
Author(s):  
Alex Gregorio Mendoza Arteaga ◽  
Gregorio Isoldo Mendoza Cedeño ◽  
Enrique Javier Macías Arias ◽  
Sandy Raúl Chun Molina
Keyword(s):  
Face Recognition ◽  
Key Words ◽  
Video Surveillance ◽  
Facial Recognition ◽  
Surveillance Systems ◽  
Biometric Recognition ◽  
Recognition Algorithms ◽  
Methods And Techniques ◽  
Automatic Systems ◽  
The Ideal

En el presente artículo se analiza la factibilidad de la implementación de algoritmos de reconocimiento facial integrados a los sistemas de video vigilancia de un territorio, para la localización de personas y como herramienta de búsqueda de individuos prófugos de la justicia convirtiéndose en un aporte importante a las investigaciones policiales y judiciales. Para alcanzar este objetivo, se estudian aristas sobre el reconocimiento biométrico y se considera el reconocimiento facial como el proceso ideal para la propuesta y discusión del artículo, en consecuencia, se investiga las etapas, métodos y técnicas más comunes y de mayor eficacia en los sistemas automáticos de reconocimiento de rostros para identificación de personas mediante imágenes y videos. Por consiguiente, se concluye que la implementación de un sistema automático de reconocimiento faciales interconectado a uno o varios sistemas de video vigilancia facilitara la búsqueda de individuos dentro del territorio donde se lo aplique.   Palabras claves: Biométrico, algoritmos, sistemas automáticos, tecnologías    Sistema de reconocimiento Facial    Systems of facial recognition, like tool for people's quest  Abstract In this article the feasibility of implementing facial recognition algorithms integrated video surveillance systems in a territory, to locate people tool analyzes and as individuals search for fugitives from justice becoming an important contribution to the police and judicial investigations. To achieve this goal, edges on biometric recognition are studied and considered facial recognition as the ideal for the proposal and discussion of Article process, therefore the steps, methods and techniques more common and more effective is investigated on the automatic face recognition to identify people through images and videos. Therefore, it is concluded that the implementation of a system of interconnected automatic facial recognition of one or several video surveillance systems facilitate finding individuals within the territory where it is applied.  Key words: Biometric, algorithms, automatic systems, technologies  

scholarly journals Comparison of Object Recognition Algorithms

2020 ◽  
pp. 21-25
Author(s):  
Gleb Popov ◽  
◽  
Tatiana Popova ◽  
Keyword(s):  
Object Recognition ◽  
Video Surveillance ◽  
Video Stream ◽  
Reference Image ◽  
Surveillance Systems ◽  
Small Object ◽  
Process Automation ◽  
Video Cameras ◽  
Recognition Algorithms ◽  
Special Points

Despite the increasing popularity of process automation, modern video surveillance systems still require constant human involvement to establish the fact of dangerous situations. But at present, systems are becoming more complex, this leads to an increase in threats and it is no longer possible for the operator to keep track of all emerging threats. In addition, in the field of video surveillance, tasks have been added that a person can no longer control just by watching video cameras. In this connection, you need to automate the process. Methods that provide maximum detection stability for small object movements, zoom changes, turning the object at a small angle, and changing lighting are based on describing the image at specific points. A special point is a point that has a number of key features that distinguish it from many other points in the image. Special points are the main characteristics of the object in the video surveillance system. The best object recognition algorithms based on this principle are the SURF and SIFT algorithms. These algorithms search for the direct occurrence of the reference image in relation to the observed one. The article discusses algorithms for detecting objects in an image based on the description of the image by special points. A comparison of SIFT and SURF algorithms, the analysis highlighted particular points in the recognition of each object, error analysis AI Node in identifying objects in the video stream.

scholarly journals Secure Video Surveillance Framework in Smart City

Sensors ◽  
2021 ◽  
Vol 21 (13) ◽  
pp. 4419
Author(s):  
Hao Li ◽  
Tianhao Xiezhang ◽  
Cheng Yang ◽  
Lianbing Deng ◽  
Peng Yi
Keyword(s):  
Video Surveillance ◽  
Smart City ◽  
Key Management ◽  
Surveillance System ◽  
Chinese Remainder Theorem ◽  
Smart Cities ◽  
Group Key Management ◽  
Video Surveillance System ◽  
Surveillance Systems ◽  
Key Update

In the construction process of smart cities, more and more video surveillance systems have been deployed for traffic, office buildings, shopping malls, and families. Thus, the security of video surveillance systems has attracted more attention. At present, many researchers focus on how to select the region of interest (RoI) accurately and then realize privacy protection in videos by selective encryption. However, relatively few researchers focus on building a security framework by analyzing the security of a video surveillance system from the system and data life cycle. By analyzing the surveillance video protection and the attack surface of a video surveillance system in a smart city, we constructed a secure surveillance framework in this manuscript. In the secure framework, a secure video surveillance model is proposed, and a secure authentication protocol that can resist man-in-the-middle attacks (MITM) and replay attacks is implemented. For the management of the video encryption key, we introduced the Chinese remainder theorem (CRT) on the basis of group key management to provide an efficient and secure key update. In addition, we built a decryption suite based on transparent encryption to ensure the security of the decryption environment. The security analysis proved that our system can guarantee the forward and backward security of the key update. In the experiment environment, the average decryption speed of our system can reach 91.47 Mb/s, which can meet the real-time requirement of practical applications.

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