Научный журнал Моделирование, оптимизация и информационные технологииThe scientific journal Modeling, Optimization and Information Technology
cетевое издание
issn 2310-6018

The architecture of software for multi-camera tracking in video surveillance systems with a decentralized structure

Nikolaev D.A.  

UDC 004.724
DOI: 10.26102/2310-6018/2020.31.4.010

  • Abstract
  • List of references
  • About authors

The article presents variant of software architectural solutions that support a special function of video analytics – multi-camera support in video surveillance systems, which based on decentralized control information exchange. Considered the main capabilities of existing hardware platforms for intelligent video surveillance cameras, as well as the analysis and generalization of existing architectures of distributed computing systems, approaches to the functional design and subsequent implementation of software modules that provide a message exchange protocol during the process of multi-camera tracking of an object are proposed. The functions of multi-camera tracking focused on the use of architecture CAN P2P network (Content Addressable Network) is highlighted. A hardware and software implementation of such network based on the CAN (Controller Area Network) protocols - C2C architecture (CAN2CAN) is proposed. The features of the implementation of software modules are determined depending on the type of control of the functions of a distributed computing system and the hardware features of intelligent video cameras. On the example of a number of practical implementations of open source software and controllers, both a generalized multi-level architecture of video analytics software for the multi-camera support function and architectural templates of modules and software that implements the decentralized interaction of a set of intelligent video cameras in the process of multi-camera support, implemented using C2C network.

1. Rinner B., Wolf W. An Introduction to Distributed Smart Cameras. IEEE Xplore. 2008;96(10):1565-1575.

2. Barthélemy J. et al. Edge-computing video analytics for real-time traffic monitoring in a smart city. Sensors. 2019;19(9):2048.

3. Quaritsch M., Kreuzthaler M., Rinner B., Bischof H., Strobl B. Autonomous Multi-Camera Tracking on Embedded Smart Cameras. EURASIP Journal on Embedded Systems. 2007;092827.

4. Rowe A., Goel D., Rajkumar R. FireFly Mosaic: A Vision-Enabled Wireless Sensor Networking System. In Proc. of the 28th IEEE International RealTime Systems Symposium RTSS 2007. D. Goel, Ed. 2007:459-468.

5. Hu P. MeshVision: an adaptive wireless mesh network video surveillance system Multimedia systems. 2010;16(4-5);243-254.

6. Fleck S., Loy R., Vollrath C., Walter F., Straßer W. SmartClassySurv – A Smart Camera Network for Distributed Tracking and Activity Recognition and its Application to Assisted Living. In Proc. of the 1st ACM/IEEE Int. Conference on Distributed Smart Cameras ICDSC ’07, Sept. 2007:211-218.

7. Prohorov P. Obosnovanie struktury programmnogo obespecheniya «umnoj» kamery videonablyudeniya. Mathematical structures and modeling. 2015;3(35):81-90.

8. Zykov V.N., Kashkovskij V.V. Issledovanie metodov obnaruzheniya ob'ektov i postroeniya traektorii ih dvizheniya v sistemah videonablyudeniya. Studencheskij. 2017;8-1:20-24.

9. Wolf W., Ozer B., Lv T. Smart Cameras as Embedded Systems. IEEE Computer. 2002;35(9):48-53.

10. Lebedenko E.V., Nikolaev D.A. Modelirovanie processa decentralizovannogo upravleniya mnogokamernym soprovozhdeniem ob'ektov v podsisteme videoanalitiki sistemy videonablyudeniya. Sistemy upravleniya i informacionnye tekhnologii. 2019;4:41-46.

11. Nikolaev D.A., Lebedenko E.V. K voprosu o modelirovanii sistem s decentralizovannym upravleniem pri mnogokamernom soprovozhdenii ob'ektov slezheniya. Informacionnye tekhnologii modelirovaniya i upravleniya. 2019;2(116):90-99.

12. Nikolaev D.A., Lebedenko E.V. K voprosu o modelirovanii sistem s decentralizovannym upravleniem pri mnogokamernom soprovozhdenii ob'ektov slezheniya. Informacionnye tekhnologii modelirovaniya i upravleniya. 2019;2(116):90-99.

13. Lebedenko E.V., Nikolaev D.A. Algoritmy decentralizovannogo upravleniya mnogokamernym soprovozhdeniem v televizionnyh ohrannyh sistemah. XI Vserossijskaya mezhvedomstvennaya nauchnaya konferenciya «Aktual'nye napravleniya razvitiya sistem ohrany, special'noj svyazi i informacii dlya nuzhd gosudarstvennogo upravleniya», Akademiya FSO Rossii. 2018.

14. Dias F., Berry F., Serot J., Marmoiton F. Hardware, Design and Implementation Issues on a Fpga-BasedSmart Camera. In Proc. of the 1st ACM/IEEE Int. Conference on Distributed Smart Cameras ICDSC ’07, Sept. 2007:20-26.

15. Smart cameras embed processor power. Available at: https://www.vision-systems.com/cameras-accessories/article/16738353/smart-cameras-embed-processor-power (accessed 16.09.2020).

16. TMDSCSK388 DM38x Camera Starter Kit (CSK). Available at: https://www.ti.com/tool/TMDSCSK388 (accessed 21.09.2020).

17. Ratnasamy S. A scalable content-addressable network. ACM. 2001;31(4):161-172.

18. ISO 11898-1:2015 Road vehicles – Controller area network (CAN) – Part 1: Data link layer and physical signalling. Available at: https://www.iso.org/standard/63648.html (accessed 15.10.2020).

19. Shcherbakov A. Protokoly prikladnogo urovnya CAN-setej. Contemporary Technologies in Automation. 1999;3:1-10.

20. PC card PCI-104 – PROFINET IO-Device. Available at: https://www.hilscher.com/products/product-groups/pc-cards/pci-104/cifx-104c-re-rpns/ (accessed 19.10.2020).

Nikolaev Dmitriy Aleksandrovich

Russian Federation Security Guard Service Federal Academy

Orel, Russian Federation

Keywords: distributed computing system, video surveillance system, decentralized control, multicamera tracking, video analytics, software, peer-to-peer network, content addressable network, packet switching

For citation: Nikolaev D.A. The architecture of software for multi-camera tracking in video surveillance systems with a decentralized structure. Modeling, Optimization and Information Technology. 2020;8(4). Available from: https://moitvivt.ru/ru/journal/pdf?id=856 DOI: 10.26102/2310-6018/2020.31.4.010 (In Russ).

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