Top

Published in:

2021 | OriginalPaper | Chapter

Detecting School Violence Using Artificial Intelligence to Interpret Surveillance Video Sequences

Authors : Sergazy Narynov, Zhandos Zhumanov, Aidana Gumar, Mariyam Khassanova, Batyrkhan Omarov

Published in: Advances in Computational Collective Intelligence

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

In this study, we present a skeleton-based approach for detecting aggressive activity. The approach does not require much powerful hardware but is very fast in realization. There are two stages in our method: feature extraction from video frames to evaluate a person’s posture, and then action classification using a neural network to determine if the frames contain bullying scenes. We also selected 13 classes for identifying aggressor’s and victim’s behavior, created a dataset of 400 min of video data that contains actions of one person and 20 h of video data containing actions of physical bullying and aggression. The approach was tested on the assembled dataset. Results show more than 97% accuracy in determining aggressive behavior in video sequences.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

previous chapter Combining Feature Extraction Methods and Principal Component Analysis for Recognition of Vietnamese Off-Line Handwritten Uppercase Accented Characters

next chapter Audio Surveillance: Detection of Audio-Based Emergency Situations

Pande, N., Karyakarte, M.: A review for semantic analysis and text document annotation using natural language processing techniques. SSRN 3418747 (2019)

Alshemali, B., Kalita, J.: Improving the reliability of deep neural networks in NLP: a review. Knowl. Based Syst. 105210 (2019)

Yankah, S., Adams, K.S., Grimes, L., Price, A.: Age and online social media behavior in prediction of social activism orientation. J. Soc. Media Soc. 6(2), 56–89 (2017)

Costello, M., Hawdon, J.: Who are the online extremists among us? Sociodemographic characteristics, social networking, and online experiences of those who produce online hate materials. Violen. Gender 5(1), 55–60 (2018)CrossRef

Ferrara, E.: Contagion dynamics of extremist propaganda in social networks. Inf. Sci. 418, 1–12 (2017)CrossRef

A Brief History of the Olweus Bullying Prevention Program. http://www.violencepreventionworks.org/public/olweus_history.page

Olweus, D.: Bully/victim problems among schoolchildren: basic facts and effects of a school based intervention program. Developm. Treat. Childhood Aggres. 17, 411–448 (1991)

Clarke, A.M., Morreale, S., Field, C., Hussein, Y., Barry, M.M.: What works in enhancing social and emotional skills development during childhood and adolescence? A review of the evidence on the effectiveness of school-based and out-of-school programmes in the UK (2015)

Chen, H.: Exploring extremism and terrorism on the web: the dark web project. In: Yang, C.C., et al. (eds.) Intelligence and Security Informatics, pp. 1–20. Springer, Heidelberg (2007). https://doi.org/10.1007/978-3-540-71549-8_1CrossRef

10.

Vasconcelos, N., Lippman, A.: Towards semantically meaningful feature spaces for the characterization of video content. Proc. Int. Conf. Image Process. 1, 25–28 (1997). https://doi.org/10.1109/ICIP.1997.647375CrossRef

11.

Clarin, C.T., Dionisio, J.A.M., Echavez, M.T., Naval, P.C.: DOVE: detection of movie violence using motion intensity analysis on skin and blood. Technical report, University of the Philippines (2005)

12.

Datta, A., Shah, M., Lobo, N.D.V.: Person-on-person violence detection in video data. Object Recogn. Supp. User Interact. Service Robots 1, 433–438 (2002). https://doi.org/10.1109/ICPR.2002.1044748CrossRef

13.

Deniz, O., Serrano, I., Bueno, G., Kim, T.: Fast violence detection in video. In: 2014 International Conference on Computer Vision Theory and Applications (VISAPP), vol. 2, pp. 478–485 (2014)

14.

Dong, Z., Qin, J., Wang, Y.: Multi-stream deep networks for person to person violence detection in videos. In: Tan, T., Li, X., Chen, X., Zhou, J., Yang, J., Cheng, H. (eds.) CCPR 2016. CCIS, vol. 662. Springer, Singapore (2016). https://doi.org/10.1007/978-981-10-3002-4CrossRef

15.

Krizhevsky, A., Sutskever, I., Hinton, G.E.: ImageNet classification with deep convolutional neural networks. In: Pereira, F., Burges, C.J.C., Bottou, L., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems, vol. 25, pp. 1097–1105. Curran Associates, Inc. (2012). http://papers.nips.cc/paper/4824-imagenetclassification-with-deep-convolutional-neural-networks.pdf

16.

Sudhakaran, S., Lanz, O.: Learning to detect violent videos using convolutional long short-term memory. CoRR abs/1709.06531 (2017). http://arxiv.org/abs/1709.06531

17.

Eknarin, D., Luepol, P., Suwatchai, K.: Video representation learning for CCTV-based violence detection. In: Proceedings of the 2018 3rd Technology Innovation Management and Engineering Science International Conference (TIMES-iCON), Bangkok, Thailand, 12–14 December 2018

18.

Sumon, S.A., Goni, R., Hashem, N.B., Shahria, T., Rahman, R.M.: Violence detection by pretrained modules with different deep learning approaches. Vietnam J. Comput. Sci. 7, 22–23 (2020)CrossRef

19.

Chen, J., Xu, Y., Zhang, C., Xu, Z., Meng, X., Wang, J.: An improved two-stream 3D convolutional neural network for human action recognition. In: Proceedings of the 2019 25th International Conference on Automation and Computing (ICAC), Lancaster, UK, 5–7 September 2019

20.

Accattoli, S., Sernani, P., Falcionelli, N., Mekuria, D.N., Dragoni, A.F.: Violence detection in videos by combining 3D convolutional neural networks and support vector machines. Appl. Artif. Intell. 34, 202–203 (2020)CrossRef

21.

Schmidt, B., Wang, L.: Automatic work objects calibration via a global–local camera system Robot. Comput. Integr. Manuf. 30, 678–683 (2014)CrossRef

22.

Paul, R.P.: Robot manipulators: mathematics, programming, and control. In: The Computer Control of Robot Manipulators Richard Paul (1981)

23.

Shiu, Y.C., Ahmad, S.: Calibration of wrist-mounted robotic sensors by solving homogeneous transform equations of the form AX = XB. IEEE Trans. Robot. Autom. 5, 16–29 (1989)CrossRef

24.

Zanchettin, A.M., Ceriani, N.M., Rocco, P., Ding, H., Matthias, B.: Safety in human-robot collaborative manufacturing environments: metrics and control. IEEE Trans. Automat. Sci. Eng. 13(2), 882–893 (2016). https://doi.org/10.1109/TASE.2015.2412256CrossRef

25.

Hornung, A., Wurm, K.M., Bennewitz, M., Stachniss, C., Burgard, W.: OctoMap: an efficient probabilistic 3D mapping framework based on octrees. Autonom. Robots 34(3), 189–206 (2013). https://doi.org/10.1007/s10514-012-9321-0CrossRef

26.

Witten, I., Frank, E., Hall, M., Pal, C.: Data Mining: Practical Machine Learning Tools and Techniques, 4th edn. Morgan Kaufmann, San Franscico (2017)

27.

Ng, A.: Machine Learning Yearning. deeplearning.ai (2018)

Title: Detecting School Violence Using Artificial Intelligence to Interpret Surveillance Video Sequences
Authors: Sergazy Narynov
Zhandos Zhumanov
Aidana Gumar
Mariyam Khassanova
Batyrkhan Omarov
Publisher: Springer International Publishing
Book: Advances in Computational Collective Intelligence
Print ISBN: 978-3-030-88112-2

Electronic ISBN: 978-3-030-88113-9

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-3-030-88113-9_32

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner