Vehicle Tracking Algorithm Based on Observation Feedback and Block Symmetry Particle Filter
This paper proposes a novel particle filter algorithm for vehicle tracking, which feeds observation information back to state model and integrates block symmetry into observation model. In view of the proposal distribution in traditional particle filter without considering the observation data, a ne...
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Format: | Article |
Language: | English |
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Wiley
2014-01-01
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Series: | Journal of Electrical and Computer Engineering |
Online Access: | http://dx.doi.org/10.1155/2014/520342 |
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author | Yanshuang Hao Yixin Yin Jinhui Lan |
author_facet | Yanshuang Hao Yixin Yin Jinhui Lan |
author_sort | Yanshuang Hao |
collection | DOAJ |
description | This paper proposes a novel particle filter algorithm for vehicle tracking, which feeds observation information back to state model and integrates block symmetry into observation model. In view of the proposal distribution in traditional particle filter without considering the observation data, a new state transition model which takes the observation into account is presented, so that the allocation of particles is more familiar with the posterior distribution. To track the vehicles in background with similar colors or under partial occlusion, block symmetry is proposed and introduced into the observation model. Experimental results show that the proposed algorithm can improve the accuracy and robustness of vehicle tracking compared with traditional particle filter and Kernel Particle Filter. |
format | Article |
id | doaj-art-b4f4b496c6d34f7d9ee4ef7565268dfb |
institution | Kabale University |
issn | 2090-0147 2090-0155 |
language | English |
publishDate | 2014-01-01 |
publisher | Wiley |
record_format | Article |
series | Journal of Electrical and Computer Engineering |
spelling | doaj-art-b4f4b496c6d34f7d9ee4ef7565268dfb2025-02-03T05:52:22ZengWileyJournal of Electrical and Computer Engineering2090-01472090-01552014-01-01201410.1155/2014/520342520342Vehicle Tracking Algorithm Based on Observation Feedback and Block Symmetry Particle FilterYanshuang Hao0Yixin Yin1Jinhui Lan2School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaSchool of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaSchool of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, ChinaThis paper proposes a novel particle filter algorithm for vehicle tracking, which feeds observation information back to state model and integrates block symmetry into observation model. In view of the proposal distribution in traditional particle filter without considering the observation data, a new state transition model which takes the observation into account is presented, so that the allocation of particles is more familiar with the posterior distribution. To track the vehicles in background with similar colors or under partial occlusion, block symmetry is proposed and introduced into the observation model. Experimental results show that the proposed algorithm can improve the accuracy and robustness of vehicle tracking compared with traditional particle filter and Kernel Particle Filter.http://dx.doi.org/10.1155/2014/520342 |
spellingShingle | Yanshuang Hao Yixin Yin Jinhui Lan Vehicle Tracking Algorithm Based on Observation Feedback and Block Symmetry Particle Filter Journal of Electrical and Computer Engineering |
title | Vehicle Tracking Algorithm Based on Observation Feedback and Block Symmetry Particle Filter |
title_full | Vehicle Tracking Algorithm Based on Observation Feedback and Block Symmetry Particle Filter |
title_fullStr | Vehicle Tracking Algorithm Based on Observation Feedback and Block Symmetry Particle Filter |
title_full_unstemmed | Vehicle Tracking Algorithm Based on Observation Feedback and Block Symmetry Particle Filter |
title_short | Vehicle Tracking Algorithm Based on Observation Feedback and Block Symmetry Particle Filter |
title_sort | vehicle tracking algorithm based on observation feedback and block symmetry particle filter |
url | http://dx.doi.org/10.1155/2014/520342 |
work_keys_str_mv | AT yanshuanghao vehicletrackingalgorithmbasedonobservationfeedbackandblocksymmetryparticlefilter AT yixinyin vehicletrackingalgorithmbasedonobservationfeedbackandblocksymmetryparticlefilter AT jinhuilan vehicletrackingalgorithmbasedonobservationfeedbackandblocksymmetryparticlefilter |