TRACKING MULTIPLE TARGETS BASED ON STEREO VISION

Ali Ganoun, Thomas Veit, Didier Aubert

2009

Abstract

This paper deals with the problem of tracking multiple objects in outdoor scenarios for the prospective of intelligent vehicles. The input of the proposed algorithm is the result of a stereovision obstacle detection algorithm. The aim is to establish the correspondence between the detected objects in consecutive frames and to reconstruct the trajectory of each individual object. To this purpose, an object model based on its scene position and its intensity caracteristic is defined. A track management strategy including track initiation, track termination and track continuation is also proposed. This strategy enables to deal with issues such as object appearance, dispapearance, occlusion and detection failure. An adaptive model update technique is applied in order to take into account appearance variations of the tracked object along time. Experiments were carried out in the context of pedestrian detection. Results on urban scenarios illustrate the performance of the proposed method.

References

  1. Bar-Shalom, Y. and Blair, W. (2000). MultitargetMultisensor Tracking: Applications and Advances, volume III. Artech House, Norwood, MA.
  2. Blackman, S. and Popoli, R. (1999). Modern Tracking Systems. Artech House Publishers Library, 2nd edition.
  3. Brown, L., Senior, A., Tian, Y.-L., Connell, J., and Hampapur, A. (2005). Performance evaluation of surveillance systems under varying conditions. In IEEE Int'l Workshop on Performance Evaluation of Tracking and Surveillance.
  4. Cox, I. and Hingorani, S. (1996). An efficient implementation of reid's multiple hypothesis tracking algorithm and its evaluation for the purpose of visual tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 18(2):138-150.
  5. Fortmann, T., Bar-Shalom, Y., and Scheffe, M. (1983). Sonar tracking of multiple targets using joint probabilistic data association. IEEE Journal of Oceanic Engineering, 8(3):173-184.
  6. Gavrila, D. and Munder, S. (2007). Multi-cue pedestrian detection and tracking from a moving vehicle. International Journal of Computer Vision, 73(1):41-59.
  7. Labayrade, R., Aubert, D., and Tarel, J.-P. (2002). Real time obstacle detection in stereovision on non flat road geometry through ”v-disparity” representation. IEEE Intelligent Vehicle Symposium, 2:646-651.
  8. Medioni, G., Cohen, I., Bremond, F., Hongeng, S., and Nevatia, R. (2001). Event detection and analysis from video streams. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(8):873-889. 0162- 8828.
  9. Muoz-Salinas, R., Aguirre, E., Garca-Silvente, M., and Gonzalez, A. (2008). A multiple object tracking approach that combines colour and depth information using a confidence measure. Pattern Recognition Letters, 29(10):1504-1514.
  10. Nummiaro, K., Koller-Meier, E., and Van Gool, L. (2003). An adaptive color-based particle filter. Image and Vision Computing, 21(1):99-110.
  11. Rasmussen, C. and Hager, G. (2001). Probabilistic data association methods for tracking complex visual objects.
  12. IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(6):560-576.
  13. Reid, D. (1979). An algorithm for tracking multiple targets. IEEE Transactions on Automatic Control, 24(6):843- 854.
  14. Scharstein, D. and Szeliski, R. (2002). A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision, 47(1):7-42.
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Paper Citation


in Harvard Style

Ganoun A., Veit T. and Aubert D. (2009). TRACKING MULTIPLE TARGETS BASED ON STEREO VISION . In Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009) ISBN 978-989-8111-69-2, pages 470-477. DOI: 10.5220/0001789404700477


in Bibtex Style

@conference{visapp09,
author={Ali Ganoun and Thomas Veit and Didier Aubert},
title={TRACKING MULTIPLE TARGETS BASED ON STEREO VISION},
booktitle={Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)},
year={2009},
pages={470-477},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001789404700477},
isbn={978-989-8111-69-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2009)
TI - TRACKING MULTIPLE TARGETS BASED ON STEREO VISION
SN - 978-989-8111-69-2
AU - Ganoun A.
AU - Veit T.
AU - Aubert D.
PY - 2009
SP - 470
EP - 477
DO - 10.5220/0001789404700477