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Estimation of the people position in the world coordinate system for video surveillance

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Abstract

A method is proposed for estimating the position of people in a scene when their head locations are known in the image plane. An extension of the approach is presented for processing several observations of the same person. It is shown that the algorithm proposed can be incorporated in the existing tracking methods involving a video from a static camera.

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References

  1. Konushin, A., Filippov, I., Konushin, V., and Kononov, V., Counting people in a video sequence based on head detection, Program. Prod. Sist., 2015, no. 1, pp. 121–126.

    Google Scholar 

  2. Shalnov, E. and Konushin, A., Human Pose Estimation in Video via MCMC Sampling, Proceedings of the 5th International Workshp on Image Mining. Theory and Applications, 2015, pp. 71–79.

    Google Scholar 

  3. Shalnov, E.V., Konushin, V.S., and Konushin, A.S. An improvement on an MCMC-based video tracking algorithm, Pattern Recognit. Image Anal., 2015, vol. 25, no. 3, pp. 532–540.

    Article  Google Scholar 

  4. Andriyenko, A., Schindler, K., and Roth, S., Discretecontinuous optimization for multi-target tracking, 2012 IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2012, pp. 1926–1933.

    Chapter  Google Scholar 

  5. Milan, A., Roth, S., and Schindler, K., Continuous energy minimization for multitarget tracking, IEEE Trans. Pattern Anal. Machine Intell., 2014, vol. 36, no. 1, pp. 58–72.

    Article  Google Scholar 

  6. Gringauz, A., Shalnov, E., and Konushin, A., Modification of the multi-target tracking algorithm based on energy minimization, GraphiCon-2014, 2014, pp. 139–142.

    Google Scholar 

  7. Batanov, P., Kononov, V., and Konushin, A., People tracking in surveillance systems for sport games using multiple cameras, Graphicon, 2013, pp. 333–336.

    Google Scholar 

  8. Baltieri, D., et al., Multi-view people surveillance using 3D information, 2011 IEEE Conf. on Computer Visions (ICCV Workshops), 2011. pp. 1817–1824.

    Chapter  Google Scholar 

  9. Berclaz, J., et al., Evaluation of probabilistic occupancy map people detection for surveillance systems, Proc. IEEE Int. Workshop on Performance Evaluation of Tracking and Surveillance, 2009, no. LIDIAP-CONF-2009-064.

    Google Scholar 

  10. Benfold, B. and Reid, I. Stable multi-target tracking in real-time surveillance video, 2011 IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2011.

    Google Scholar 

  11. Keni, B. and Rainer, S., Evaluating multiple object tracking performance: the CLEAR MOT metrics, EURASIP J. Image Video Process., 2008.

    Google Scholar 

  12. Hartley, R. and Zisserman, A., Multiple View Geometry in Computer Vision, Cambridge: Cambridge Univ. Press, 2003.

    MATH  Google Scholar 

  13. Kononov, V., Konushin, V., and Konushin, A., People Tracking Algorithm for Human Height Mounted Cameras, Proc. 33rd Symp. of the German Association for Pattern Recognition (DAGM 2011), 2011, pp. 163–72.

    Google Scholar 

  14. Chetverikov, N. and Konushin, A., Finding objects in a video stream using graph cuts, Graphicon, 2012, pp. 262–265.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Graphics an Media Laboratory, Faculty of Computational Mathematics and Cybernetics, Moscow State University, Moscow, 119991, Russia

    E. V. Shal’nov, A. D. Gringauz & A. S. Konushin

Authors
  1. E. V. Shal’nov
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  2. A. D. Gringauz
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  3. A. S. Konushin
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Corresponding author

Correspondence to E. V. Shal’nov.

Additional information

Original Russian Text © E.V. Shal’nov, A.D. Gringauz, A.S. Konushin, 2016, published in Programmirovanie, 2016, Vol. 42, No. 6.

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Shal’nov, E.V., Gringauz, A.D. & Konushin, A.S. Estimation of the people position in the world coordinate system for video surveillance. Program Comput Soft 42, 361–366 (2016). https://doi.org/10.1134/S0361768816060062

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  • DOI: https://doi.org/10.1134/S0361768816060062

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