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Mathematical Problems in Engineering
Volume 2015, Article ID 545204, 9 pages
http://dx.doi.org/10.1155/2015/545204
Research Article

Dynamic Track Management in MHT for Pedestrian Tracking Using Laser Range Finder

1Vehicle System Engineering Research Lab, Universiti Teknologi Malaysia, Jalan Semarak, 54100 Kuala Lumpur, Malaysia
2Department of Precision Engineering, Tokai University, Hiratsuka 259-1292, Japan

Received 28 August 2014; Accepted 5 November 2014

Academic Editor: Yudong Zhang

Copyright © 2015 Abdul Hadi Abd Rahman et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. T. Zhao, R. Nevatia, and B. Wu, “Segmentation and tracking of multiple humans in crowded environments,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 30, no. 7, pp. 1198–1211, 2008. View at Publisher · View at Google Scholar · View at Scopus
  2. F.-M. Chang and F.-L. Lian, “Polar grid based robust pedestrian tracking with indoor mobile robot using multiple hypothesis tracking algorithm,” in Proceedings of the 51st Annual Conference on of the Society of Instrument and Control Engineers of Japan (SICE '12), pp. 1558–1563, Akita, Japan, August 2012. View at Scopus
  3. K. O. Arras, Ó. M. Mozos, and W. Burgard, “Using boosted features for the detection of people in 2D range data,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '07), pp. 3402–3407, IEEE, April 2007. View at Publisher · View at Google Scholar · View at Scopus
  4. A. Carballo, A. Ohya, and S. Yuta, “Reliable people detection using range and intensity data from multiple layers of laser range finders on a mobile robot,” International Journal of Social Robotics, vol. 3, no. 2, pp. 167–186, 2011. View at Publisher · View at Google Scholar · View at Scopus
  5. P. Kondaxakis, S. Kasderidis, and P. Trahanias, “A multi-target tracking technique for mobile robots using a laser range scanner,” in Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS '08), pp. 3370–3377, September 2008. View at Publisher · View at Google Scholar · View at Scopus
  6. K. Klasing, D. Wollherr, and M. Buss, “Realtime segmentation of range data using continuous nearest neighbors,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA '09), pp. 2431–2436, May 2009. View at Publisher · View at Google Scholar · View at Scopus
  7. K. Wenzl, H. Ruser, and C. Kargel, “Performance evaluation of a decentralized multitarget-tracking algorithm using a LIDAR sensor network with stationary beams,” IEEE Transactions on Instrumentation and Measurement, vol. 62, no. 5, pp. 1174–1182, 2013. View at Publisher · View at Google Scholar · View at Scopus
  8. Y. Zhang, S. Wang, P. Phillips, and G. Ji, “Binary PSO with mutation operator for feature selection using decision tree applied to spam detection,” Knowledge-Based Systems, vol. 64, pp. 22–31, 2014. View at Publisher · View at Google Scholar · View at Scopus
  9. Y. Zhang, S. Wang, Y. Huo, L. Wu, and A. Liu, “Feature extraction of brain MRI by stationary wavelet transform and its applications,” Journal of Biological Systems, vol. 18, no. 1, pp. 115–132, 2010. View at Publisher · View at Google Scholar · View at Scopus
  10. R. Ding and W.-H. Chen, “Moving object tracking in support of unmanned vehicle opeartion,” in Proceedings of the 19th International Conference on Automation and Computing (ICAC '13), pp. 1–6, IEEE, London, UK, September 2013. View at Scopus
  11. S. Coraluppi, “Multi-stage multiple-hypothesis tracking,” Journal of Advances in Information Fusion, vol. 6, no. 1, pp. 57–68, 2011. View at Google Scholar
  12. J. R. Vasquez and J. L. Williams, “Improved hypothesis selection for multiple hypothesis tracking,” in Signal and Data Processing of Small Targets, vol. 5428 of Proceedings of SPIE, 2005. View at Publisher · View at Google Scholar
  13. D. Mohammed, K. Mokhtar, O. Abdelaziz, and M. Abdelkrim, “A new IMM algorithm using fixed coefficients filters (fastIMM),” AEU—International Journal of Electronics and Communications, vol. 64, no. 12, pp. 1123–1127, 2010. View at Publisher · View at Google Scholar · View at Scopus
  14. S. S. Blackman, “Multiple hypothesis tracking for multiple target tracking,” IEEE Aerospace and Electronic Systems Magazine, vol. 19, no. 1, pp. 5–18, 2004. View at Publisher · View at Google Scholar · View at Scopus
  15. T.-D. Vu, J. Burlet, and O. Aycard, “Grid-based localization and local mapping with moving object detection and tracking,” Information Fusion, vol. 12, no. 1, pp. 58–69, 2011. View at Publisher · View at Google Scholar · View at Scopus
  16. J. Xavier, M. Pacheco, D. Castro, A. Ruanot, and U. Nunes, “Fast line, arc/circle and leg detection from laser scan data in a player driver,” in Proceedings of the IEEE International Conference on Robotics and Automation, pp. 3930–3935, IEEE, April 2005. View at Publisher · View at Google Scholar · View at Scopus
  17. D. B. Reid, “An algorithm for tracking multiple targets,” IEEE Transactions on Automatic Control, vol. 24, no. 6, pp. 843–854, 1979. View at Google Scholar · View at Scopus
  18. M. A. Zakaria, H. Zamzuri, R. Mamat, and S. A. Mazlan, “A path tracking algorithm using future prediction control with spike detection for an autonomous vehicle robot,” International Journal of Advanced Robotic Systems, vol. 10, article 309, 9 pages, 2013. View at Publisher · View at Google Scholar