Tracking Pedestrians across Multiple Microcells Based on Successive Bayesian Estimations
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, s...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/719029 |
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| _version_ | 1832555406360051712 |
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| author | Yoshiaki Taniguchi Masahiro Sasabe Takafumi Watanabe Hirotaka Nakano |
| author_facet | Yoshiaki Taniguchi Masahiro Sasabe Takafumi Watanabe Hirotaka Nakano |
| author_sort | Yoshiaki Taniguchi |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-1a24932a4eb1457c983a5ccd97103614 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-1a24932a4eb1457c983a5ccd971036142025-02-03T05:48:18ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/719029719029Tracking Pedestrians across Multiple Microcells Based on Successive Bayesian EstimationsYoshiaki Taniguchi0Masahiro Sasabe1Takafumi Watanabe2Hirotaka Nakano3Faculty of Science and Engineering, Kindai University, Higashiosaka 577-8502, JapanNara Institute of Science and Technology, Ikoma 630-0192, JapanGraduate School of Information Science and Technology, Osaka University, Suita 565-0871, JapanCybermedia Center, Osaka University, Toyonaka 560-0043, JapanWe 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.http://dx.doi.org/10.1155/2014/719029 |
| spellingShingle | Yoshiaki Taniguchi Masahiro Sasabe Takafumi Watanabe Hirotaka Nakano Tracking Pedestrians across Multiple Microcells Based on Successive Bayesian Estimations The Scientific World Journal |
| title | Tracking Pedestrians across Multiple Microcells Based on Successive Bayesian Estimations |
| title_full | Tracking Pedestrians across Multiple Microcells Based on Successive Bayesian Estimations |
| title_fullStr | Tracking Pedestrians across Multiple Microcells Based on Successive Bayesian Estimations |
| title_full_unstemmed | Tracking Pedestrians across Multiple Microcells Based on Successive Bayesian Estimations |
| title_short | Tracking Pedestrians across Multiple Microcells Based on Successive Bayesian Estimations |
| title_sort | tracking pedestrians across multiple microcells based on successive bayesian estimations |
| url | http://dx.doi.org/10.1155/2014/719029 |
| work_keys_str_mv | AT yoshiakitaniguchi trackingpedestriansacrossmultiplemicrocellsbasedonsuccessivebayesianestimations AT masahirosasabe trackingpedestriansacrossmultiplemicrocellsbasedonsuccessivebayesianestimations AT takafumiwatanabe trackingpedestriansacrossmultiplemicrocellsbasedonsuccessivebayesianestimations AT hirotakanakano trackingpedestriansacrossmultiplemicrocellsbasedonsuccessivebayesianestimations |