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Mathematical Problems in Engineering
Volume 2015 (2015), Article ID 545204, 9 pages
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.


Real time pedestrian tracking could be one of the important features for autonomous navigation. Laser Range Finder (LRF) produces accurate pedestrian data but a problem occurs when a pedestrian is represented by multiple clusters which affect the overall tracking process. Multiple Hypothesis Tracking (MHT) is a proven method to solve tracking problem but suffers a large computational cost. In this paper, a multilevel clustering of LRF data is proposed to improve the accuracy of a tracking system by adding another clustering level after the feature extraction process. A Dynamic Track Management (DTM) is introduced in MHT with multiple motion models to perform a track creation, association, and deletion. The experimental results from real time implementation prove that the proposed multiclustering is capable of producing a better performance with less computational complexity for a track management process. The proposed Dynamic Track Management is able to solve the tracking problem with lower computation time when dealing with occlusion, crossed track, and track deletion.