Advertisement

Vehicle Detection and Tracking for Traffic Monitoring

  • Gian Luca Foresti
  • Lauro Snidaro
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)

Abstract

This paper addresses some of the indications of the European Union for road safety by proposing a real-time traffic monitoring system for vehicle detection and tracking in bad illuminated scenarios. Several urban and extra-urban roads during the night or tunnels are characterized by low illumination, light spots, shadows, light reflections, etc. The main objectives of the proposed system are: (a) to monitor the traffic flow, (b) to estimate the vehicle’s speed or determine the state of the traffic, (c) to detect anomalous situations, e.g. rising alarms in case of road accidents or stopped cars. Experimental results on real image sequences demonstrate the effectiveness of the proposed system.

Keywords

Light Spot Vehicle Detection Traffic Monitoring Minimum Bound Rectangle Vehicle Tracking 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Foresti, G.L., Regazzoni, C.S., Varshney, P.K.: Multisensor Surveillance Systems:The Fusion Perspective. Kluwer Academic Publishers, Dordrecht (2003)Google Scholar
  2. 2.
    Grace, A.E., Pycock, D., Tillotson, H.T., Snaith, M.S.: Active shape from stereo for highway inspection. Machine Vision and Applications 12(1), 7–15 (2000)CrossRefGoogle Scholar
  3. 3.
    Aoky, M.: Imaging and analysis of traffic scene. In: Int. Conf. on Image Processing, Kobe, Japan, October 1999, pp. 28–32 (1999)Google Scholar
  4. 4.
    D’Agostino, S.: Commercial machine vision system for traffic monitoring and control. In: SPIE, vol. 1615, pp. 180–186 (1991)Google Scholar
  5. 5.
    Foresti, G.L.: Real-time detection of multiple moving objects in complex image sequences. Int. Journal of Imaging Systems and Technology 10, 305–317 (1999)CrossRefGoogle Scholar
  6. 6.
    Bullock, D., Mantri, S.: Multimedia data model for video detection research. Journal of Transportation Engineering 121(5), 385–390 (1995)CrossRefGoogle Scholar
  7. 7.
    Yuan, X., Lu, Y.-J., Sarraf, S.: Computer vision system for automatic vehicle classification. Journal of Transportation Engineering 120(6), 861–876 (1994)CrossRefGoogle Scholar
  8. 8.
    Zhu, Z., Xu, G., Yang, B., Shi, D., Lin, X.: VISATRAM: a real-time vision system for automatic traffic monitoring. Image and Vision Computing 18(10), 781–794 (2000)CrossRefGoogle Scholar
  9. 9.
    Online White Paper: European transport policy for 2010: time to decide (2001), http://europa.eu.int/comm/energy_transport/en/lb_en.html

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Gian Luca Foresti
    • 1
  • Lauro Snidaro
    • 1
  1. 1.Department of Mathematics and Computer ScienceUniversity of UdineUdineItaly

Personalised recommendations