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Defining Crowd Movement as Parabola and Classifying These Definitions

Year 2016, Special Issue (2016), 165 - 169, 01.12.2016
https://doi.org/10.18100/ijamec.269245

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.

References

  • [1] 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.
  • [2] 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.
  • [3] 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.
  • [4] 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.
  • [5] 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.
  • [6] 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
  • [7] 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.
  • [8] A.Dehghan M.M.Kalayeh, Understanding Crowd Collectivity: A Meta-Tracking Approach IEEE International Conference on Computer Vision and Pattern Recognition Workshop(CVPRW) 2015
  • [9] Bolei Zhou, Xiaoou Tang, and Xiaogang Wang, Measuring Crowd Collectiveness, IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2013.
Year 2016, Special Issue (2016), 165 - 169, 01.12.2016
https://doi.org/10.18100/ijamec.269245

Abstract

References

  • [1] 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.
  • [2] 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.
  • [3] 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.
  • [4] 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.
  • [5] 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.
  • [6] 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
  • [7] 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.
  • [8] A.Dehghan M.M.Kalayeh, Understanding Crowd Collectivity: A Meta-Tracking Approach IEEE International Conference on Computer Vision and Pattern Recognition Workshop(CVPRW) 2015
  • [9] Bolei Zhou, Xiaoou Tang, and Xiaogang Wang, Measuring Crowd Collectiveness, IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2013.
There are 9 citations in total.

Details

Subjects Engineering
Journal Section Research Article
Authors

Murat Akpulat

Murat Ekinci

Publication Date December 1, 2016
Published in Issue Year 2016 Special Issue (2016)

Cite

APA Akpulat, M., & Ekinci, M. (2016). Defining Crowd Movement as Parabola and Classifying These Definitions. International Journal of Applied Mathematics Electronics and Computers(Special Issue-1), 165-169. https://doi.org/10.18100/ijamec.269245
AMA Akpulat M, Ekinci M. Defining Crowd Movement as Parabola and Classifying These Definitions. International Journal of Applied Mathematics Electronics and Computers. December 2016;(Special Issue-1):165-169. doi:10.18100/ijamec.269245
Chicago Akpulat, Murat, and Murat Ekinci. “Defining Crowd Movement As Parabola and Classifying These Definitions”. International Journal of Applied Mathematics Electronics and Computers, no. Special Issue-1 (December 2016): 165-69. https://doi.org/10.18100/ijamec.269245.
EndNote Akpulat M, Ekinci M (December 1, 2016) Defining Crowd Movement as Parabola and Classifying These Definitions. International Journal of Applied Mathematics Electronics and Computers Special Issue-1 165–169.
IEEE M. Akpulat and M. Ekinci, “Defining Crowd Movement as Parabola and Classifying These Definitions”, International Journal of Applied Mathematics Electronics and Computers, no. Special Issue-1, pp. 165–169, December 2016, doi: 10.18100/ijamec.269245.
ISNAD Akpulat, Murat - Ekinci, Murat. “Defining Crowd Movement As Parabola and Classifying These Definitions”. International Journal of Applied Mathematics Electronics and Computers Special Issue-1 (December 2016), 165-169. https://doi.org/10.18100/ijamec.269245.
JAMA Akpulat M, Ekinci M. Defining Crowd Movement as Parabola and Classifying These Definitions. International Journal of Applied Mathematics Electronics and Computers. 2016;:165–169.
MLA Akpulat, Murat and Murat Ekinci. “Defining Crowd Movement As Parabola and Classifying These Definitions”. International Journal of Applied Mathematics Electronics and Computers, no. Special Issue-1, 2016, pp. 165-9, doi:10.18100/ijamec.269245.
Vancouver Akpulat M, Ekinci M. Defining Crowd Movement as Parabola and Classifying These Definitions. International Journal of Applied Mathematics Electronics and Computers. 2016(Special Issue-1):165-9.

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