Robust Vehicle Tracking Multi-feature Particle Filter

  • M. Eren Yildirim
  • Jongkwan Song
  • Jangsik Park
  • Byung Woo Yoon
  • Yunsik Yu
Part of the Communications in Computer and Information Science book series (CCIS, volume 263)


Object detection and tracking have been studied separately in most cases. Particle filtering has proven very successful for non-linear and non-Gaussian estimation problems. This paper presents a new method for tracking moving vehicles with temporal disappearance. The proposed method can continue tracking after disappearance. Color distribution of objects is integrated into particle filtering algorithm. As the color of an object can vary over time dependent on the illumination, a likelihood model is used including color cue and detection cue. Color cue is provided by using Bhattacharyya distance, and detection cue is provided by Euclidean distance. Tests are made by using highway cameras that are located on bridge.


Particle filtering Color distribution Euclidean distance Bhattacharyya distance 


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  1. 1.
    Black, M.J., Jepson, A.D.: A Probabilistic Framework for Matching Temporal Trajectories: CONDENSATION-Based Recognition of Gestures and Expressions. In: Burkhardt, H.-J., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1406, pp. 909–924. Springer, Heidelberg (1998)Google Scholar
  2. 2.
    Beymer, D., McLauchlan, P., Coifman, B., Malik, J.: A Real-time Computer Vision System for Measuring Traffic Parameters. In: Computer Vision and Pattern Recognition, pp. 495–501 (1997)Google Scholar
  3. 3.
    Greiffenhagen, M., Ramesh, V., Comaniciu, D., Niemann, H.: Statistical Modeling and Performance Characterization of a Real-Time Dual Camera Surveillance System. In: Computer Vision and Pattern Recognition, pp. 335–342 (2000)Google Scholar
  4. 4.
    Menser, B., Brünig, M.: Face Detection and Tracking for Video Coding Applications. In: Asil omar Conference on Signals, Systems, and Computers, pp. 49–53 (2000)Google Scholar
  5. 5.
    Segen, J., Pingali, S.: A Camera-Based System for Tracking People in Real Time. In: International Conference on Pattern Recognition, pp. 63–67 (1996)Google Scholar
  6. 6.
    Djuric, P.M., Kotecha, J.H., Zhang, J., Huang, Y., Ghirmai, T., Bugallo, M.F., Miguez, J.: Particle Filtering. IEEE Signal Processing Magazine (2003) 1053-5888/03Google Scholar
  7. 7.
    Isard, M., Blake, A.: Contour Tracking by Stochastic Propagation of Conditional Density. In: European Conference on Computer Vision, pp. 343–356 (1996)Google Scholar
  8. 8.
    Isard, M., Blake, A.: CONDENSATION – Conditional Density Propagation for Visual Tracking. International Journal on Computer Vision 1(29), 5–28 (1998)CrossRefGoogle Scholar
  9. 9.
    Comaniciu, D., Ramesh, V., Meer, P.: Real-Time Tracking of Non- Rigid Objects using Mean Shift. In: Computer Vision and Pattern Recognition, pp. 142–149 (2000)Google Scholar
  10. 10.
    Nummiaro, K., Koller-Meier, E., Gool, L.V.: An Adaptive Color-Based Particle Filter. Elsevier Science (2002)Google Scholar
  11. 11.
    Aherne, F., Thacker, N., Rockett, P.: The Bhattacharyya Metric as an Absolute Similarity Measure for Frequency Coded Data. Kybernetika 32(4), 1–7 (1997)MathSciNetzbMATHGoogle Scholar
  12. 12.
    Kailath, T.: The Divergence and Bhattacharyya Distance Measures in Signal Selection. IEEE Transactions on Communication Technology COM 15(1), 52–60 (1967)CrossRefGoogle Scholar
  13. 13.
    Jia, Y., Qu, W.: Real-Time Integrated Multi-Object Detection and Tracking in Video Sequences Using Detection and Mean Shift Based Particle Filters. IEEE, 978-1-4244-6359-6/10Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • M. Eren Yildirim
    • 1
  • Jongkwan Song
    • 1
  • Jangsik Park
    • 1
  • Byung Woo Yoon
    • 1
  • Yunsik Yu
    • 2
  1. 1.Department of Electronics EngineeringKyungsung UniversityBusanKorea
  2. 2.Convergence of IT Devices Institute BusanBusanKorea

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