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The Scientific World Journal
Volume 2014, Article ID 719029, 7 pages
Research Article

Tracking Pedestrians across Multiple Microcells Based on Successive Bayesian Estimations

1Faculty of Science and Engineering, Kindai University, Higashiosaka 577-8502, Japan
2Nara Institute of Science and Technology, Ikoma 630-0192, Japan
3Graduate School of Information Science and Technology, Osaka University, Suita 565-0871, Japan
4Cybermedia Center, Osaka University, Toyonaka 560-0043, Japan

Received 8 March 2014; Accepted 28 July 2014; Published 11 August 2014

Academic Editor: Juan M. Corchado

Copyright © 2014 Yoshiaki Taniguchi 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.


We propose a method for tracking multiple pedestrians using a binary sensor network. In our proposed method, sensor nodes are composed of pairs of binary sensors and placed at specific points, referred to as gates, where pedestrians temporarily change their movement characteristics, such as doors, stairs, and elevators, to detect pedestrian arrival and departure events. Tracking pedestrians in each subregion divided by gates, referred to as microcells, is conducted by matching the pedestrian gate arrival and gate departure events using a Bayesian estimation-based method. To improve accuracy of pedestrian tracking, estimated pedestrian velocity and its reliability in a microcell are used for trajectory estimation in the succeeding microcell. Through simulation experiments, we show that the accuracy of pedestrian tracking using our proposed method is improved by up to 35% compared to the conventional method.