ISSN 2071-8594

Russian academy of sciences

Editor-in-Chief

Gennady Osipov

A. D. Ulyev, V. L. Rozaliev, A. V. Zaboleeva-Zotova, Y. A. Orlova Intelligent Video Surveillance System for Human Behavior

Abstract.

The paper describes an intelligent video surveillance system for human behavior and provides a brief overview of systems with similar functional characteristics. We present a collection of methods and algorithms for automatic recognition of human images, their identification, and analysis of behavior based on motor activity using a cascade of neural networks. A technology for capturing a person's image and tracking their movements between video cameras is proposed.

Keywords:

video image, human posture recognition, motor activity, behavior monitoring, intelligent system, artificial neural networks.

PP. 21-32.

DOI 10.14357/20718594200403

References

1. Dopolnyaya intellekt [Complementing intelligence]. URL: https://ntechlab.ru/ (accessed: 09.03.2020).
2. Videonablyudenie v aeroportu [Airport video surveillance]. URL: https://cabling.ru/otraslevye-resheniya/videonablyudenie-v-aeroporte/ (accessed: 31.03.2020).
3. Podschet lyudej dlya prinyatiya obosnovanny`x reshenij [Counting people to make informed decisions]. URL: https://www.axis.com/ru-ru/products/axis-people-counter (accessed: 31.03.2020).
4. Sistema podscheta posetitelej [Visitor counting system]. URL: https://www.watcom.ru/products/sistema_podscheta_posetiteley/ (accessed: 31.03.2020).
5. Zaboleeva-Zotova A.V., Bobkov A.S., Orlova Y.A., Rozaliev V.L., Polovinkin A.I. Automated identification of human emotions based on analysis of body move-ments// Proceedings of the IADIS International Conferences - Interfaces and Human Computer Interaction 2013, IHCI 2013 and Game and Entertainment Technologies 2013. 2013. P 299-304.
6. Cao Z., Simon T., Wie S.-E., Sheikh Y. Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields. URL: http://arxiv.org/abs/1611.08050 (accessed: 31.03.2020).
7. Insafutdinov E., Pishchulin L., Andres B., Andriluka M., Schiele B. Deepercut: A deeper, stronger, and faster multi-person pose estimation model. URL: https://arxiv.org/pdf/1605.03170 (accessed: 31.03.2020).
8. Primenenie raspoznavaniya licz v razlichny`x scenariyax [Application of face recognition in various scenarios]. URL: https://azure.microsoft.com/ru-ru/services/cognitive-services/face/#demo (accessed: 31.03.2020).
9. Zaboleeva-Zotova A.V., Bobkov A.S., Rozaliev V.L., Petrovsky A.B. Automated identification of human emotions by gestures and poses // Proceedings - 1st BRICS Countries Congress on Computational Intelligence, BRICS-CCI 2013. 2013. P. 300-303.
10. Kanazawa A., Black M.J., Jacobs D.V., Malik J. End-to-end Recovery of Human Shape and Pose. URL: https://arxiv.org/abs/1712.06584v1 (accessed: 31.03.2020).
11. Iqbal U., Gall J. Multi-person pose estimation with local joint-to-person associations. URL: https//arxiv.org/abs/1608.08526v2 (accessed: 31.03.2020).
12. Cao Z., Simon T., Wei S.-E., Sheikh Y. Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields. URL: https://arxiv.org/abs/1611.08050v2 (accessed: 31.03.2020).
13. Osipova Y.A., Lavrov D.N. Primenenie klasternogo analiza metodom k-srednih dlya klassifikacii tekstov nauchnoj napravlennosti [Application of cluster analysis by k-means method for classification of scientific texts]// Matematicheskie struktury` i modelirovanie [Mathemati-cal Structures and Modeling]. 2017. No. 3. P. 108-121.
14. Khorunsjiy M.D. Metod kolichestvennoi otsenki tsvetovykh razlichii v vospriyatii tsifrovykh izobrazhenii [The method of quantitative estimation of color differences in the perception of digital images]// Vestnik NGU. Seriya: Informacionny`e texnologii [Vestnik NSU. Series: Information Technologies]. 2008. No. 1. P. 80-88.
15. Ulyanova O.А. Psihologicheskie osobennosti prodavcov_konsultantov setevogo marketinga [Psychological features of network marketing sales consultants]// Vestnik Samarskoj gumanitarnoj akademii. Seriya: Psixologiya. [Samara Academy of Humanities. Series: Psychology]. 2013. No. 1. P. 27-41.
16. Moskvin A.A., Shishkin A.G. Primenenie metodov glubokogo obucheniya dlya raspoznavaniya e`mocional`nogo sostoyaniya cheloveka na videoizobrazhenii [Application of deep learning methods for recognizing the emotional state of a person on video images] // Iskusstvennyj intellekt i prinyatie reshenij [Artificial intelligence and decision making]. 2019. No. 2. P. 3-14.
17. Rozaliev V., Guschin R., Orlova Yu., Zaboleeva-Zotova A., Berdnik V. The method for searching emotional content in images based on low-level parameters with using neural networks // Advances in Intelligent Systems and Computing. 2019. No. 848. P. 260-265.