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A Particle Filtering and DSmT Based Approach for Conflict Resolving in case of Target Tracking with Multiple Cues

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Abstract

In this paper, we propose an efficient and robust method for multiple targets tracking in cluttered scenes using multiple cues. Our approach combines the use of Monte Carlo sequential filtering for tracking and Dezert-Smarandache theory (DSmT) to integrate the information provided by the different cues. The use of DSmT provides the necessary framework to quantify and overcome the conflict that might appear between the cues due to the occlusion. Our tracking approach is tested with color and location cues on a cluttered scene where multiple targets are involved in partial or total occlusion.

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References

  1. Stringa, E., Regazzoni, C.S.: Real-time video shot detection for scene surveillance applications. IEEE Trans. Image Process. 9, 69–79 (2000)

    Article  Google Scholar 

  2. Czyz, J., Ristic, B., Macq, B.: A particle filter for joint detection and tracking of color objects. Image Vis. Comput. 25(8), 1271–1281 (2007)

    Article  Google Scholar 

  3. Yang, Y., Teoh, E.K., Shen, D.: Lane detection and tracking using B-Snake. Image Vis. Comput. 22(4), 269–280 (2004)

    Article  Google Scholar 

  4. Chen, C., Lin, X., Shi, Y.: Moving object tracking under varying illumination conditions. Patern Recogn. Lett. 27(14), 1632–1643 (2006)

    Article  Google Scholar 

  5. Frank, O., Nieto, J., Guivant, J., Scheding, S.: Multiple target tracking using sequential Monte Carlo methods and statistical data association. In: Proc. of the IEEE Int. C. on Intell. Rob. and Syst., vol. 3, pp. 2718–2723 (2003)

  6. Schultz, D., Burgard, W., Fox, D., Cremers, A.B.: Tracking multiple moving targets with a mobile robot using particle filters and statistical data association. In: Proc. of IEEE Int. C. on Rob. and Auto., vol. 1, pp. 1665–1670 (2001)

  7. Ozyilidiz, E., Krahnstover, N., Sharma, R.: Adaptive texture and color segmentation for tracking moving objects. Patern Recogn. 35(10), 2013–2029 (2002)

    Article  Google Scholar 

  8. McCane, B., Galvin, B., Novins, K.: Algorithmic fusion for more robust feature tracking. Int. J. Comput. Vis. 49(1), 79–89 (2002)

    Article  MATH  Google Scholar 

  9. Dewasurendra, D.A., Bauer, P.H., Premaratne, K.: Evidence filtering. IEEE Trans. Signal Process. 55(12), 5796–5805 (2007)

    Article  MathSciNet  Google Scholar 

  10. Ramasso, E., Panagiotakis, C., Pellerin, D., Rombaut, M.: Human action recognition in videos based on the transferable belief model: application to athletics jumps. Pattern Anal. Appl. 11(1), 1–19 (2008)

    Article  MathSciNet  Google Scholar 

  11. Ramasso, E., Rombaut, M., Pellerin, D.: Forward-Backword Viterbi procedures in the transferable belief model for state sequence analysis using belief functions. Lect. Notes Artif. Intell. 4724, 405–417 (2007)

    Google Scholar 

  12. Shafer, G.: A Mathematical Theory of Evidence. Princeton University Press, Princeton (1976)

    MATH  Google Scholar 

  13. Smarandache, F., Dezert, J.: Applications and Advances of DSmT for Information Fusion. Am. Res. Press, Rehoboth (2004)

    MATH  Google Scholar 

  14. Comtet, L.: Sperner Systems. Reidel, Dordrecht (1974), pp. 271–273

    Google Scholar 

  15. Arulampalam, M.S., Maskell, S., Gordon, N., Clapp, T.: A tutorial on particle filters for online nonlinear/non-Gaussian Bayesian tracking. IEEE Trans. Signal Process. 50(2), 174–188 (2002)

    Article  Google Scholar 

  16. Hue, C., Cadre, J.-P.L., Perez, P.: Tracking multiple objects with particle filtering. IEEE Trans. Aerosp. Electron. Syst. 38(3), 791–812 (2002)

    Article  Google Scholar 

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Correspondence to Layachi Bentabet.

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Sun, Y., Bentabet, L. A Particle Filtering and DSmT Based Approach for Conflict Resolving in case of Target Tracking with Multiple Cues. J Math Imaging Vis 36, 159–167 (2010). https://doi.org/10.1007/s10851-009-0178-6

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  • DOI: https://doi.org/10.1007/s10851-009-0178-6

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