Skip to main content
SpringerLink
Log in

A Novel Decentralised System Architecture for Multi-camera Target Tracking

  • Conference paper
  • First Online:
Advanced Concepts for Intelligent Vision Systems (ACIVS 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10016))

Abstract

Target tracking in a multi-camera system is an active and challenging research that in many systems requires video synchronisation and knowledge of the camera set-up and layout. In this paper a highly flexible, modular and decentralised system architecture is presented for multi-camera target tracking with relaxed synchronisation constraints among camera views. Moreover, the system does not rely on positional information to handle camera hand-off events. As a practical application, the system itself can, at any time, automatically select the best target view available, to implicitly solve occlusion. Further, to validate the proposed architecture, an extension to a multi-camera environment of the colour-based IMS-SWAD tracker is used. The experimental results show that the tracker can successfully track a chosen target in multiple views, in both indoor and outdoor environments, with non-overlapping and overlapping camera views.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight 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

References

  1. Smeulders, A., Chu, D., Cucchiara, R., Calderara, S., Dehghan, A., Shah, M.: Visual tracking: an experimental survey. IEEE Trans. Pattern Anal. Mach. Intell. 36(7), 1442–1468 (2014)

    Article  Google Scholar 

  2. Wang, X.: Intelligent multi-camera video surveillance: a review. Pattern Recogn. Lett. 34(1), 3–19 (2013)

    Article  Google Scholar 

  3. Collins, R.T., Lipton, A.J., Fujiyoshi, H., Kanade, T.: Algorithms for cooperative multisensor surveillance. Proc. IEEE 89(10), 1456–1477 (2001)

    Article  Google Scholar 

  4. Tron, R., Vidal, R.: Distributed computer vision algorithms. IEEE Sig. Process. Mag. 28(3), 32–45 (2011)

    Article  Google Scholar 

  5. Remagnino, P., Shihab, A.I., Jones, G.A.: Distributed intelligence for multi-camera visual surveillance. Pattern Recogn. 37(4), 675–689 (2004). Elsevier

    Article  Google Scholar 

  6. Taj, M., Cavallaro, A.: Distributed and decentralized multicamera tracking. IEEE Sig. Process. Mag. 28(3), 46–58 (2011)

    Article  Google Scholar 

  7. Ercan, A., Gamal, A., Guibas, L.: Object tracking in the presence of occlusions using multiple cameras: a sensor network approach. ACM Trans. Sen. Netw. 9(2), 16:1–16:36 (2013)

    Article  Google Scholar 

  8. Javed, O., Shafique, K., Rasheed, Z., Shah, M.: Modeling intercamera spacetime and appearance relationships for tracking across nonoverlapping views. Comput. Vis. Image Underst. 109(2), 146–162 (2008)

    Article  Google Scholar 

  9. Lobaton, E., Vasudevan, R., Bajcsy, R., Sastry, S.: A distributed topological camera network representation for tracking applications. IEEE Trans. Image process. 19(10), 2516–2529 (2010)

    Article  MathSciNet  Google Scholar 

  10. Porikli, F., Divakaran, A.: Multi-camera calibration, object tracking and query generation. In: International Conference on Multimedia and Expo I, pp. 653–656 (2003)

    Google Scholar 

  11. Moller, B., Plotz, T., Fink, G.A.: Calibration-free camera handover for fast and reliable person tracking in multi-camera setups. In: International Conference on Pattern Recognition, pp. 1–4 (2008)

    Google Scholar 

  12. Di Caterina, G., Soraghan, J.: A robust, precise and flexible tracking algorithm based on IMS and SWAD. In: IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 6588–6592 (2014)

    Google Scholar 

  13. Adam, A., Rivlin, E., Shimshoni, I., Reinitz, D.: Robust real-time unusual event detection using multiple fixed-location monitors. IEEE Trans. Pattern Anal. Mach. Intell. 30(3), 555–560 (2008)

    Article  Google Scholar 

  14. D’Orazio, T., Guaragnella, C.: A survey of automatic event detection in multi-camera third generation surveillance systems. Int. J. Pattern Recogn. Artif. Intell. 29(1), 1–29 (2015). 1555001

    Google Scholar 

  15. Di Caterina, G., Soraghan, J.J.: An abandoned and removed object detection algorithm in a reactive smart surveillance system. In: International Conference on Digital Signal Processing, pp. 1–6 (2011)

    Google Scholar 

  16. Buchsbaum, G.: A spatial processor model for object colour perception. J. Franklin Inst. 310(1), 1–26 (1980)

    Article  MathSciNet  Google Scholar 

  17. PETS2009: Benchmark data. http://www.cvg.reading.ac.uk/PETS2009/a.html. Accessed 14 May 2016

Download references

Author information

Authors and Affiliations

  1. Department of Electronic and Electrical Engineering, University of Strathclyde, 204 George Street, Glasgow, G1 1XW, UK

    Gaetano Di Caterina, Trushali Doshi, John J. Soraghan & Lykourgos Petropoulakis

Authors
  1. Gaetano Di Caterina
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Trushali Doshi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. John J. Soraghan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Lykourgos Petropoulakis
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Trushali Doshi .

Editor information

Editors and Affiliations

  1. Université Paris-Sud 11 , Orsay, France

    Jacques Blanc-Talon

  2. University of Salento , Lecce, Lecce, Italy

    Cosimo Distante

  3. Ghent University , Gent, Belgium

    Wilfried Philips

  4. CSIRO ICT Centre , Sydney, New South Wales, Australia

    Dan Popescu

  5. University of Antwerp , Wilrijk, Belgium

    Paul Scheunders

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing AG

About this paper

Cite this paper

Di Caterina, G., Doshi, T., Soraghan, J.J., Petropoulakis, L. (2016). A Novel Decentralised System Architecture for Multi-camera Target Tracking. In: Blanc-Talon, J., Distante, C., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2016. Lecture Notes in Computer Science(), vol 10016. Springer, Cham. https://doi.org/10.1007/978-3-319-48680-2_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-48680-2_9

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-48679-6

  • Online ISBN: 978-3-319-48680-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation