Journal of Engineering and Applied Sciences

Year: 2017
Volume: 12
Issue: 21
Page No. 5467 - 5472

Distance and Speed Based Anomaly Detection in Human Crowd Movement

Authors : Sanchit Sharma, Anshul Sharma and Nitish Ojha

References

Adam, A., E. Rivlin, I. Shimshoni and D. Reinitz, 2008. Robust real-time unusual event detection using multiple fixed-location monitors. IEEE. Trans. Pattern Anal. Mach. Intell., 30: 555-560.
CrossRef  |  PubMed  |  Direct Link  |  

Ali, S. and M. Shah, 2007. A lagrangian particle dynamics approach for crowd flow segmentation and stability analysis. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June 17-22, 2007, IEEE, Miami, Florida, USA., ISBN:1-4244-1179-3, pp: 1-6.

Andrade, E.L., S. Blunsden and R.B. Fisher, 2006. Modelling crowd scenes for event detection. Proceedings of the 18th International Conference on Pattern Recognition, Volume 1, August 20-24, 2006, Hong Kong, pp: 175-178.

Chebi, H. and D. Acheli, 2015. Dynamic detection of anomalies in crowd's behavior analysis. Proceedings of the 2015 4th International Conference on Electrical Engineering (ICEE), December 13-15, 2015, IEEE, Boumerdes, Algeria, ISBN:978-1-4673-6673-1, pp: 1-5.

Ke, Y., R. Sukthankar and M. Hebert, 2007. Event detection in crowded videos. Proceedings of thr IEEE 11th International Conference on Computer Vision ICCV, October 14-21, 2007, IEEE, Rio de Janeiro, Brazil, ISBN:978-1-4244-1630-1, pp: 1-8.

Khan, M.T., A. Ali, M.Y. Durrani and I. Siddiqui, 2015. Survey of holistic crowd analysis models. J. Comput. Sci. Commun., 1: 1-9.

Kratz, L. and K. Nishino, 2009. Anomaly detection in extremely crowded scenes using spatio-temporal motion pattern models. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June 20-25, 2009, Miami, FL., USA., pp: 1446-1453.

Kumar, M.P., P.H. Torr and A. Zisserman, 2008. Learning layered motion segmentations of video. Int. J. Comput. Vision, 76: 301-319.
CrossRef  |  

Meena, M.K., S. Meena and R. Sikarwar, 2013. Detection of position and posture of occupants using low resolution sensor. Intl. J. Comput. Commun. Networking, 2: 33-35.
Direct Link  |  

Mehran. R, A. Oyama and M. Shah, 2009. Abnormal crowd behavior detection using social force model. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, June 20-25, 2009, Miami, FL., USA., pp: 935-942.

Nguyen, H.T., Q. Ji and A.W. Smeulders, 2007. Spatio-temporal context for robust multitarget tracking. IEEE. Trans. Pattern Anal. Mach. Intell., 29: 52-64.
CrossRef  |  PubMed  |  Direct Link  |  

Sharif, M.H., S. Uyaver and C. Djeraba, 2010. Crowd behavior surveillance using Bhattacharyya distance metric. Proceedings of the 2nd International Symposium on Computational Modeling of Objects Represented in Images, May 5-7, 2010, Springer, Buffalo, New York, USA., pp: 311-323.

Tang, X., S. Zhang and H. Yao, 2013. Sparse coding based motion attention for abnormal event detection. Proceedings of the 2013 20th IEEE International Conference on Image Processing (ICIP), September 15-18, 2013, IEEE, Melbourne, Victoria, Australia, ISBN:978-1-4799-2341-0, pp: 3602-3606.

Tu, P., T. Sebastian, G. Doretto, N. Krahnstoever and J. Rittscher et al., 2008. Unified crowd segmentation. Proceedings of the 10th International European Conference on Computer Vision, Computer Vision-ECCV, October 12-18, 2008, Springer, Marseille, France, pp: 691-704.

Unnikrishnan, A., F. Ajesh and R.S. Nair, 2015. Detection of abnormal visual events using HOFO and KNN. Intl. J. Inf. Futuristic Res., 2: 3196-3210.
Direct Link  |  

Wang, B., M. Ye, X. Li and F. Zhao, 2011. Abnormal crowd behavior detection using size-adapted spatio-temporal features. Intl. J. Control, Autom. Syst., 9: 905-912.
Direct Link  |  

Zerdi, N., S. Kulkarni and V.D. Mytri, 2014. Crowd behaviour analysis and classification using graph theory. Intl. J. Ethics Eng. Manage. Educ., 1: 175-179.
Direct Link  |  

Zerdi, N., S.S. Kulkarni, V.D. Mytri and K.D. Dhruve, 2014. Crowd behavior analysis and classification using graph theoretic approach. Global J. Comput. Sci. Technol., 14: 25-34.
Direct Link  |  

Zhong, H., J. Shi and M. Visontai, 2004. Detecting unusual activity in video. Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition CVPR Vol. 2, June 27- July 2, 2004, IEEE, Washington, DC, USA., ISBN:0-7695-2158-4, pp: II-819-II-826.

Zhou, S., W. Shen, D. Zeng and Z. Zhang, 2015. Unusual event detection in crowded scenes by trajectory analysis. Proceedings of the 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), April 19-24, 2015, IEEE, Brisbane, Queensland, Australia, ISBN:978-1-4673-6997-8, pp: 1300-1304.

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