Optimal Camera Placement based Resolution Requirements for Surveillance Applications

Houari Bettahar, Yacine Morsly, Mohand Said Djouadi

2014

Abstract

In this paper, we focus on the problem of optimally placing a mixture of static and PTZ cameras based on the resolution requirement, this configuration will be useful later cameras planning. The static cameras used for detecting an object or an event, this result is used to select the best PTZ camera within the network to identify or recognize this moving object or event. In our work the monitoring area is represented by a grid of points distributed uniformly or randomly (S. Thrun, 2002), then using surface-projected monitoring area and camera sensing model we develop a binary integer programming algorithm. The results of the algorithm are applied successfully to a variety of simulated scenarios.

References

  1. E. Dunn, G. Olague, and E. Lutton. (2006). Parisian Camera Placement for Vision Metrology,. Pattern Recognition Letters, 27, 1209-1219.
  2. E. Horster and R. Lienhart. (2006). Approximating Optimal Visual Sensor Placement. IEEE International Conference on Multimedia and Expo, 1257-1260.
  3. J. Urrutia. (2000). Art Gallery and Illumination Problems. in Handbook of Computational Geometry, 973-1027.
  4. J. Wangand and N. Zhong. (2006). Efficient Point Coverage in Wireless Sensor Networks. Journal of Combinatorial Optimization, 11, 291- 304.
  5. K. Chakrabarty, H. Qi, and E. Cho. (2002). Grid Coverage for Surveillanceand Target Location in Distributed Sensor Networks. Computers, IEEE Transactions, 51, 1448-1453.
  6. Morsly, Y ; Aouf, N ; Djouadi, M.S and Richardson, M. t. (2012). Particle swarm optimization inspired probability algorithm for optimal camera network placemen. IEEE Sens .J, 12, 1402-1412.
  7. R. Lienhart and E. Horster. (2006). On the Optimal Placement of MultipleVisual Sensor. in 4 th ACM International Workshop on Video Surveillanceand Sensor Networks, 111-120.
  8. S. Chen and Y. Li . (2004). Automatic Sensor Placement for Model-Based Robot Vision. Systems, Man and Cybernetics IEEE Trans Syst, 33, 393-408.
  9. S. S. Dhillon and K. Chakrabarty. (2003). Sensor Placement for Effective Coverage andSurveillanceinDistributedSensor Networks. Wireless Communications and Networking WCNCIEEE,, 3, 1609-1614.
  10. S. Thrun. (2002). Learning Occupancy Grids with Forward Sensor Models. Autonomous Robots, 15, 111-127.
  11. U. Murat and S. Sclaroff. (2006). Automated Camera Layout to SatisfyTask-Specific and Floor PlanSpecific Coverage Requirements. Computer Vision and Image Understanding, 103, 156-169.
  12. X. Chen and J. Davis. ( 2000). Camera Placement Considering Occlusion for Robust Motion Capture. Stanford University, Tech. Rep. CS-TR-2000-07.
Download


Paper Citation


in Harvard Style

Bettahar H., Morsly Y. and Djouadi M. (2014). Optimal Camera Placement based Resolution Requirements for Surveillance Applications . In Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-758-039-0, pages 252-258. DOI: 10.5220/0005046302520258


in Bibtex Style

@conference{icinco14,
author={Houari Bettahar and Yacine Morsly and Mohand Said Djouadi},
title={Optimal Camera Placement based Resolution Requirements for Surveillance Applications },
booktitle={Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2014},
pages={252-258},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005046302520258},
isbn={978-989-758-039-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 11th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - Optimal Camera Placement based Resolution Requirements for Surveillance Applications
SN - 978-989-758-039-0
AU - Bettahar H.
AU - Morsly Y.
AU - Djouadi M.
PY - 2014
SP - 252
EP - 258
DO - 10.5220/0005046302520258