On Board Camera Perception and Tracking of Vehicles

Juan Manuel Collado, Cristina Hilario, Jose Maria Armingol, Arturo de la Escalera

2007

Abstract

In this paper a visual perception system for Intelligent Vehicles is presented. The goal of the system is to perceive the surroundings of the vehicle looking for other vehicles. Depending on when and where they have to be detected (overtaking, at long range) the system analyses movement or uses a vehicle geometrical model to perceive them. Later, the vehicles are tracked. The algorithm takes into account the information of the road lanes in order to apply some geometric restrictions. Additionally, a multi-resolution approach is used to speed up the algorithm allowing real-time working. Examples of real images show the validation of the algorithm.

References

  1. H. Mori, N. M. Charkari, and T. Matsushita, On-line vehicle and pedestrian detections based on sign pattern, IEEE Trans. on Industrial Electronics, vol 41, pp. 384-391, 1994.
  2. T. Zielke, M. Brauckmann, and W. Von Seelen, Intensity and edge-based symmetry detection with application to car-following, CVGIP: Image Understanding, vol. 58, pp. 177-190, 1993.
  3. C. Goerick, D. Noll, and M. Werner, Artificial Neural Networks in Real Time Car detection and Tracking Applications, Pattern Recognition Letters, vol. 17, pp. 335-343, 1996.
  4. T.K. ten Kate, M.B. van Leewen, S.E. Moro-Ellenberger, B.J.F. Driessen, A.H.G. Versluis, and F.C.A. Groen, Mid-range and Distant Vehicle Detection with a Mobile Camera, IEEE Intelligent Vehicles Symp. 2004
  5. Broggi, P. Cerri, and P.C. Antonello, Multi-Resolution Vehicle Detection using Artificial Vision, IEEE Intelligent Vehicles Symp. 2004.
  6. M. Betke, E. Haritaoglu, and L.S. Davis, Real-time multiple vehicle detection and tracking from a moving vehicle, Machine Vision and Applications, vol. 12, pp. 69-83, 2000.
  7. JM. Ferryman, S.J. Maybank, and A.D. Worrall, Visual surveillance for moving vehicles, International Journal of Computer Vision, vol. 37, pp. 187-97, 2000
  8. T. Kato, Y. Ninomiya, and I. Masaki, Preceding vehicle recognition based on learning from sample images, IEEE Trans. on Intelligent Transportation Systems, vol. 3, pp. 252-260, 2002.
  9. Z. Sun, G. Bebis, and R. Miller, On-Road Vehicle Detection Using Optical Sensors: A Review, IEEE Intelligent Transportation Systems Conf. 2004.
  10. Wohler, and J.K. Anlauf, Real-time object recognition on image sequences with adaptable time delay neural network algorithm-applications for autonomous vehicles, Image and Vision Computing, vol. 19, pp. 593-618, 2001.
  11. P. Batavia, D. Pomerleau, and C. Thorpe, Overtaking Vehicle Detection Using Implicit Optical Flow, IEEE Transportation Systems Conf. 1997.
  12. Y. Zu, D. Comaniciu, M. Pellkofer, and and T. Koehler, Passing Vehicle Detection from Dynamic Background Using Robust information Fusion, IEEE Intelligent Transportation Systems Conf. 2004.
  13. G. Stein, O. Mano, and A. Shashua, Vision-based ACC with a Single Camera: bounds on Range and Range Rate Accuracy, IEEE Intelligent Vehicles Symp. 2003.
  14. J. M. Collado, C. Hilario, A. De la Escalera, J.M. Armingol. Self-calibration of an OnBoard Stereo-Vision System for Driver Assistance Systems, IEEE Intelligent Vehicle Symp. 2006.
  15. Hilario, J. M. Collado, J. Mª Armingol,A. de la Escalera, Pyramidal Image Analysis for Vehicle Detection, IEEE Intelligent Vehicles Symp. 2005.
Download


Paper Citation


in Harvard Style

Manuel Collado J., Hilario C., Maria Armingol J. and de la Escalera A. (2007). On Board Camera Perception and Tracking of Vehicles . In Robot Vision - Volume 1: Robot Vision, (VISAPP 2007) ISBN 978-972-8865-76-4, pages 57-66. DOI: 10.5220/0002066600570066


in Bibtex Style

@conference{robot vision07,
author={Juan Manuel Collado and Cristina Hilario and Jose Maria Armingol and Arturo de la Escalera},
title={On Board Camera Perception and Tracking of Vehicles},
booktitle={Robot Vision - Volume 1: Robot Vision, (VISAPP 2007)},
year={2007},
pages={57-66},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002066600570066},
isbn={978-972-8865-76-4},
}


in EndNote Style

TY - CONF
JO - Robot Vision - Volume 1: Robot Vision, (VISAPP 2007)
TI - On Board Camera Perception and Tracking of Vehicles
SN - 978-972-8865-76-4
AU - Manuel Collado J.
AU - Hilario C.
AU - Maria Armingol J.
AU - de la Escalera A.
PY - 2007
SP - 57
EP - 66
DO - 10.5220/0002066600570066