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The Scientific World Journal
Volume 2013 (2013), Article ID 187479, 10 pages
Research Article

Bayesian Estimation-Based Pedestrian Tracking in Microcells

1The Cybermedia Center, Osaka University, Toyonaka 560-0043, Japan
2Graduate School of Engineering, Osaka University, Suita 565-0871, Japan
3Graduate School of Information Science and Technology, Osaka University, Suita 565-0871, Japan

Received 8 July 2013; Accepted 21 August 2013

Academic Editors: S. H. Rubin and S. Sun

Copyright © 2013 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 consider a pedestrian tracking system where sensor nodes are placed only at specific points so that the monitoring region is divided into multiple smaller regions referred to as microcells. In the proposed pedestrian tracking system, sensor nodes composed of pairs of binary sensors can detect pedestrian arrival and departure events. In this paper, we focus on pedestrian tracking in microcells. First, we investigate actual pedestrian trajectories in a microcell on the basis of observations using video sequences, after which we prepare a pedestrian mobility model. Next, we propose a method for pedestrian tracking in microcells based on the developed pedestrian mobility model. In the proposed method, we extend the Bayesian estimation to account for time-series information to estimate the correspondence between pedestrian arrival and departure events. Through simulations, we show that the tracking success ratio of the proposed method is increased by 35.8% compared to a combinatorial optimization-based tracking method.