Abstract
This paper presents a multiple target tracking method that uses the Dezert-Smarandache Theory (DSmT) for data association. A detailed framework is developed to show how the DSmT can be used to associate measurements with the corresponding correct targets. We will discuss the choices of the tracking hypotheses in the DSmT and we will demonstrate the effectiveness of the developed approach on simulated and real tracking scenarios that uses color and infrared cues.
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References
Bar-Shalom, Y.: Multitarget-Multisensor Tracking: Advanced Applications. Artech House (1990)
Bar-Shalom, Y., Dale Blair, W.: Multitarget-Multisensor Tracking: Application and Advances, vol. III. Artech House, Massachusetts (2000)
Blackman, S.S.: Multiple hypotheses tracking for multiple target tracking. IEEE A&E Systems Magazine 19(1), 5–15 (2004)
Frank, O., Nieto, J., Guivant, J., Scheding, S.: Multiple target tracking using sequential Monte Carlo Methods and statistical data association. In: Proceedings of the IEEE International Conference on Intelligence Robotics and Systems, vol. 3, pp. 2718–2723 (2003)
Vermaak, J., Godsill, S., Pérez, P.: Monte Carlo Filtering for Multi-Target Tracking and data association. IEEE Trans. Aerosp. Electron. Syst. 41(1), 309–332 (2005)
Shafer, G.: A Mathematical Theory of Evidence. Princeton University Press, Princeton (1976)
Smarandache, F., Dezert, J.: Advances and applications of DSmT for information Fusion. Collected works, vol. 3. Am. Res. Press, ARP (2009)
Sun, Y., Bentabet, L.: A particle filtering and DSmT Based Approach for conflict resolving in case of Target Tracking with multiple cues. J. Math. Imag. Vis. 36(2), 159–167 (2010)
Airouche, M., Bentabet, L., Zelmat, M., Gao, G.: Pedestrian tracking using color, thermal and location cue measurements: a DSmT-based framework. Machine Vision and Applications (2011), doi: 10.1007/s00138-011-0342-z
Dang, H., Han, C.: Multi-target data association approach for vehicle tracking in road situation. In: Proceedings of IEEE on Intelligent Transportation Systems, vol. 1, pp. 379–383 (2003)
Dezert, J., Tchamova, A., Smarandache, F., Konstantinova, P.: Target Type Tracking with different fusion rules: A Comparative Analysis. In: Application and Advances of DSmT for Information Fusion, vol. 2, ch. 13. American Research Press (2006)
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© 2012 Springer-Verlag Berlin Heidelberg
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Airouche, M., Bentabet, L., Zelmat, M. (2012). A DSmT-Based Approach for Data Association in the Context of Multiple Target Tracking. In: Su, CY., Rakheja, S., Liu, H. (eds) Intelligent Robotics and Applications. ICIRA 2012. Lecture Notes in Computer Science(), vol 7507. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33515-0_67
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DOI: https://doi.org/10.1007/978-3-642-33515-0_67
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33514-3
Online ISBN: 978-3-642-33515-0
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