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2020 | OriginalPaper | Buchkapitel

A Comparative Analysis of Different Violence Detection Algorithms from Videos

verfasst von : Piyush Vashistha, Juginder Pal Singh, Mohd Aamir Khan

Erschienen in: Advances in Data and Information Sciences

Verlag: Springer Singapore

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Abstract

There are different methods or techniques used for identifying violence from video, such as hitting some object, kicking, fighting, and punching someone but still there is a big challenge for us to identify violence. However, some of the earlier mechanism generally extract descriptors around the spatiotemporal interesting points (STIP) or extract statistic features but there is limited effectiveness in detecting video-based violence. Therefore, the objective is to develop a better violence identification system that identifies the violence and triggers an alarm so that prompt assistance will be provided. This paper helps researchers who wish to study violent activity recognition and gather different insights on the main challenges and issues to solve in this emerging field.

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Literatur
1.
Zurück zum Zitat Ahonen, T., Hadid, A., & Pietikäinen, M. (2004). Face recognition with local binary patterns. In European Conference on Computer Vision (pp. 469–481). Springer. Ahonen, T., Hadid, A., & Pietikäinen, M. (2004). Face recognition with local binary patterns. In European Conference on Computer Vision (pp. 469–481). Springer.
2.
Zurück zum Zitat Arceda, V. M., Fabián, K.F., & Gutíerrez, J. C. (2016). Real time violence detection in video. Arceda, V. M., Fabián, K.F., & Gutíerrez, J. C. (2016). Real time violence detection in video.
3.
Zurück zum Zitat Cai, H., Jiang, H., Huang, X., Yang, J., & He, X. (2018). Violence detection based on spatio-temporal feature and fisher vector. In Chinese Conference on Pattern Recognition and Computer Vision (PRCV) (pp. 180–190). Springer. Cai, H., Jiang, H., Huang, X., Yang, J., & He, X. (2018). Violence detection based on spatio-temporal feature and fisher vector. In Chinese Conference on Pattern Recognition and Computer Vision (PRCV) (pp. 180–190). Springer.
4.
Zurück zum Zitat Chen, Y., Zhang, L., Lin, B., Xu, Y., & Ren, X. (2011). Fighting detection based on optical flow context histogram. In 2011 Second International Conference on Innovations in Bio-inspired Computing and Applications (pp. 95–98). IEEE. Chen, Y., Zhang, L., Lin, B., Xu, Y., & Ren, X. (2011). Fighting detection based on optical flow context histogram. In 2011 Second International Conference on Innovations in Bio-inspired Computing and Applications (pp. 95–98). IEEE.
5.
Zurück zum Zitat Datta, A., Shah, M., & Lobo, N. D. V. (2002). Person-on-person violence detection in video data. In Proceedings of 16th International Conference on Pattern Recognition (Vol. 1, pp. 433–438). IEEE. Datta, A., Shah, M., & Lobo, N. D. V. (2002). Person-on-person violence detection in video data. In Proceedings of 16th International Conference on Pattern Recognition (Vol. 1, pp. 433–438). IEEE.
6.
Zurück zum Zitat Fu, E. Y., Huang, M. X., Leong, H. V., & Ngai, G. (2018). Cross-species learning: A low-cost approach to learning human fight from animal fight. In: 2018 ACM Multimedia Conference on Multimedia Conference (pp. 320–327). ACM. Fu, E. Y., Huang, M. X., Leong, H. V., & Ngai, G. (2018). Cross-species learning: A low-cost approach to learning human fight from animal fight. In: 2018 ACM Multimedia Conference on Multimedia Conference (pp. 320–327). ACM.
7.
Zurück zum Zitat Fu, E. Y., Leong, H. V., Ngai, G., & Chan, S. (2015). Automatic fight detection based on motion analysis. In: 2015 IEEE International Symposium on Multimedia (ISM) (pp. 57–60). IEEE. Fu, E. Y., Leong, H. V., Ngai, G., & Chan, S. (2015). Automatic fight detection based on motion analysis. In: 2015 IEEE International Symposium on Multimedia (ISM) (pp. 57–60). IEEE.
8.
Zurück zum Zitat Fu, E. Y., Va Leong, H., Ngai, G., & Chan, S. (2016). Automatic fight detection in surveillance videos. In: Proceedings of the 14th International Conference on Advances in Mobile Computing and Multi Media (pp. 225–234). ACM. Fu, E. Y., Va Leong, H., Ngai, G., & Chan, S. (2016). Automatic fight detection in surveillance videos. In: Proceedings of the 14th International Conference on Advances in Mobile Computing and Multi Media (pp. 225–234). ACM.
9.
Zurück zum Zitat Gao, Y., Liu, H., Sun, X., Wang, C., & Liu, Y. (2016). Violence detection using oriented violent flows. Image and Vision Computing, 48, 37–41.CrossRef Gao, Y., Liu, H., Sun, X., Wang, C., & Liu, Y. (2016). Violence detection using oriented violent flows. Image and Vision Computing, 48, 37–41.CrossRef
10.
Zurück zum Zitat Hassner, T., Itcher, Y., & Kliper-Gross, O. (2012). Violent flows: Real-time detection of violent crowd behavior. In: 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (pp. 1–6). IEEE. Hassner, T., Itcher, Y., & Kliper-Gross, O. (2012). Violent flows: Real-time detection of violent crowd behavior. In: 2012 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (pp. 1–6). IEEE.
11.
Zurück zum Zitat Moreira, D., Avila, S., Perez, M., Moraes, D., Testoni, V., Valle, E., et al. (2019). Multimodal data fusion for sensitive scene localization. Information Fusion, 45, 307–323.CrossRef Moreira, D., Avila, S., Perez, M., Moraes, D., Testoni, V., Valle, E., et al. (2019). Multimodal data fusion for sensitive scene localization. Information Fusion, 45, 307–323.CrossRef
12.
Zurück zum Zitat Nanni, L., Brahnam, S., & Lumini, A. (2011). Local ternary patterns from three orthogonal planes for human action classification. Expert Systems with Applications, 38(5), 5125–5128.CrossRef Nanni, L., Brahnam, S., & Lumini, A. (2011). Local ternary patterns from three orthogonal planes for human action classification. Expert Systems with Applications, 38(5), 5125–5128.CrossRef
13.
Zurück zum Zitat Nievas, E. B., Suarez, O. D., García, G. B., & Sukthankar, R. (2011). Violence detection in video using computer vision techniques. In International Conference on Computer Analysis of Images and Patterns (pp. 332–339). Springer. Nievas, E. B., Suarez, O. D., García, G. B., & Sukthankar, R. (2011). Violence detection in video using computer vision techniques. In International Conference on Computer Analysis of Images and Patterns (pp. 332–339). Springer.
14.
Zurück zum Zitat Tay, N. C., Connie, T., Ong, T. S., Goh, K. O. M., & Teh, P. S. (2019). A robust abnormal behavior detection method using convolutional neural network. In Computational Science and Technology (pp. 37–47). Springer. Tay, N. C., Connie, T., Ong, T. S., Goh, K. O. M., & Teh, P. S. (2019). A robust abnormal behavior detection method using convolutional neural network. In Computational Science and Technology (pp. 37–47). Springer.
15.
Zurück zum Zitat Vashistha, P., Bhatnagar, C., & Khan, M. A. (2018). An architecture to identify violence in video surveillance system using vif and lbp. In 2018 4th International Conference on Recent Advances in Information Technology (RAIT) (pp. 1–6). IEEE. Vashistha, P., Bhatnagar, C., & Khan, M. A. (2018). An architecture to identify violence in video surveillance system using vif and lbp. In 2018 4th International Conference on Recent Advances in Information Technology (RAIT) (pp. 1–6). IEEE.
16.
Zurück zum Zitat Yang, Z., & Rothkrantz, L. J. (2010). Automatic aggression detection inside trains. In 2010 IEEE International Conference on Systems, Man and Cybernetics (pp. 2364–2372). IEEE. Yang, Z., & Rothkrantz, L. J. (2010). Automatic aggression detection inside trains. In 2010 IEEE International Conference on Systems, Man and Cybernetics (pp. 2364–2372). IEEE.
17.
Zurück zum Zitat Zhang, T., Jia, W., Gong, C., Sun, J., & Song, X. (2018). Semi-supervised dictionary learning via local sparse constraints for violence detection. Pattern Recognition Letters, 107, 98–104.CrossRef Zhang, T., Jia, W., Gong, C., Sun, J., & Song, X. (2018). Semi-supervised dictionary learning via local sparse constraints for violence detection. Pattern Recognition Letters, 107, 98–104.CrossRef
Metadaten
Titel
A Comparative Analysis of Different Violence Detection Algorithms from Videos
verfasst von
Piyush Vashistha
Juginder Pal Singh
Mohd Aamir Khan
Copyright-Jahr
2020
Verlag
Springer Singapore
DOI
https://doi.org/10.1007/978-981-15-0694-9_54

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