Skip to main content

Single Camera Multiplexing for Multi-Target Tracking

  • Chapter
Multimedia Video-Based Surveillance Systems

Abstract

Recent years have seen a continued increase in the need for, and use of automatic video surveillance, both in urban (civilian) and military airborne applications. A surveillance system is typically comprised of one or more video sensors (such as cameras), each of which is mounted on a mobile pan/tilt platform. Because the platform hardware is expensive, making the most use out of each sensor is a worthy goal. To this end, we consider the design of a novel real-time surveillance system that uses a single camera equipped with pan/tilt and zoom capabilities, to ‘keep track’ of as many targets as possible for as long as possible.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Y. Bar-Shalom and T. E. Fortmann, Tracking and Data Association, Academic Press, New York, NY, 1988.

    MATH  Google Scholar 

  2. C. Brown, “Gaze Controls with Interactions and Delays”, IEEE Transactions on Systems, Man, and Cybernetics.

    Google Scholar 

  3. R. G. Brown and P. Y. C. Hwang, Introduction to Random Signals and Applied Kalman Filtering, John Wiley & Sons, New York, 1983.

    Google Scholar 

  4. I. Cohen and G. Medioni, “Detecting and Tracking Moving Objects for Video Surveillance”, in IEEE Proc. Computer Vision and Pattern Recognition, June 1999.

    Google Scholar 

  5. I. J. Cox, “A Review of Statistical Data Association Techniques for Motion Correspondence”, International Journal of Computer Vision, Vol. 1, No. 10, pp. 53–66, 1993.

    Article  Google Scholar 

  6. A. Gelb, Applied Optimal Estimation, MIT Press, Cambridge MA, 1974.

    Google Scholar 

  7. I. Haritaoglu, D. Harwood, and L. S. Davis, “W4S: A Real-Time System for Detecting and Tracking People in 21/2 D”, in Proc. Europeen Conf. Computer Vision, June 1998.

    Google Scholar 

  8. S. Haykin, Adaptive Filter Theory, Prentice Hall, Englewood Cliffs, New Jersey, 1986.

    Google Scholar 

  9. D. Huttenlocher, J. Noh, and W. Rucklidge, “Tracking non-rigid objects in complex scenes”, in Proc. Int. Conf. Computer Vision, May 1993.

    Google Scholar 

  10. M. Isard and A. Blake, “Condensation-conditional density propagation for visual tracking”, International Journal of Computer Vision, No. 15, pp. 234–244, 1998.

    Google Scholar 

  11. R. Jain, The Art of Computer Systems Performance Analysis Techniques for Experimental Design, Measurement, Simulation, and Modeling, John Wiley & Sons, 1991.

    Google Scholar 

  12. E. Lazowska, J. Zahorjan, G. S. Graham, and K. Sevcik, Quantitative System Performance, Prentice-Hall, Inc, Englewood Cliffs, New Jersey, 1984.

    Google Scholar 

  13. T. Matsuyama, “Cooperative Distributed Vision — Dynamic Integration of Visual Perception, Action, and Communication-”, in Proc. Int. Conf. Computer Vision, 1998.

    Google Scholar 

  14. N. Papanikolopoulos, P. K. Koshla, and T. Kanade, “Vision and Control Techniques for Robotic Visual Tracking” in Proc. IEEE Int. Conf. Robotics and Automation, April 1991.

    Google Scholar 

  15. e. a. Wixson, L., “Image Alignment for Precise Camera Fixation and Aim”, in Proc. Conf. Computer Vision and Pattern Recognition, 1998.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2000 Springer Science+Business Media New York

About this chapter

Cite this chapter

Benabdelkader, C., Burlina, P., Davis, L. (2000). Single Camera Multiplexing for Multi-Target Tracking. In: Foresti, G.L., Mähönen, P., Regazzoni, C.S. (eds) Multimedia Video-Based Surveillance Systems. The Springer International Series in Engineering and Computer Science, vol 573. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4327-5_12

Download citation

  • DOI: https://doi.org/10.1007/978-1-4615-4327-5_12

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4613-6943-1

  • Online ISBN: 978-1-4615-4327-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics