Defining Crowd Movement as Parabola and Classifying These Definitions

Authors

  • Murat AKPULAT
  • Murat EKINCI

DOI:

https://doi.org/10.18100/ijamec.269245

Keywords:

Crowd Analysis, Particle Advection, Optical flow

Abstract

Smart surveillance systems developed in recent years have made enormous contributions to providing safety and management of crowds. The aim of this study is to observe and try to understand how crowd movements presented in a video sequence show behaviour. For this end, the motion data at pixel level among the consecutive frames is obtained using optical flow initially. Then, this motion data is associated using the particle advection method and stable as well as moving areas in the image are obtained. After, the moving areas clustered using Mean-Shift method are described and classified as parabola, in addition to the studies in the literature. At the end of the study, the method developed was tested over UCF as well as Pets2009 datasets and the results are presented.

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References

C. S. Jacques Junior, S. R. Musse, and C. R. Jung, Crowd analysis using computer vision techniques, IEEE Signal Processing Magazine,vol. 27, no. 5, pp. 66–77, 2010.

B. Zhan, D. N. Monekosso, P. Remagnino, S. A. Velastin, and L. Xu, Crowd analysis: a survey, Machine Vision and Applications, vol. 19,no. 5-6, pp. 345–357, 2008.

N. Sjarif, S. Shamsuddin, and S. Hashim, Detection of abnormal behaviors in crowd scenes: a review, International Journal of Advances in Soft Computing and Its Applications, vol. 3, no. 3, pp. 1–33, 2011.

M. Thida, Y. Yong, P. Climent-Prez, H.-l. Eng, and P. Remagnino, A literature review on video analytics of crowded scenes, Intelligent Multimedia Surveillance. Springer Berlin Heidelberg, 2013, pp. 17–36.

T. Li, H. Chang, M. Wang, B. Ni, R. Hong, and S. Yan, Crowded Scene Analysis: A Survey, IEEE Transactions on Circuits and Systems for Video Technology, 2015.

B.T.Morris, M.M.Trivedi, A Survey of Vision-BasedTrajectory Learning and Analysis for Surveillance, IEEE Transactions on Circuits and Systems For Video Technology

M. Hu, A. Saad and M. Shah, Learning Motion Patterns in Crowded Scenes Using Motion Flow Field, in 19th International Conference on Pattern Recognition, ICPR, 2008.

A.Dehghan M.M.Kalayeh, Understanding Crowd Collectivity: A Meta-Tracking Approach IEEE International Conference on Computer Vision and Pattern Recognition Workshop(CVPRW) 2015

Bolei Zhou, Xiaoou Tang, and Xiaogang Wang, Measuring Crowd Collectiveness, IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2013.

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Published

01-12-2016

Issue

Section

Research Articles

How to Cite

[1]
“Defining Crowd Movement as Parabola and Classifying These Definitions”, J. Appl. Methods Electron. Comput., pp. 165–169, Dec. 2016, doi: 10.18100/ijamec.269245.

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