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Multiple target tracking under occlusions using modified Joint Probabilistic Data Association

Identifieur interne : 003466 ( Hal/Corpus ); précédent : 003465; suivant : 003467

Multiple target tracking under occlusions using modified Joint Probabilistic Data Association

Auteurs : Xiufang Shi ; Ye-Qiong Song ; Zaiyue Yang ; Jiming Chen

Source :

RBID : Hal:hal-01246931

Abstract

The size of target will induce a degradation of tracking performance, which has been neglected for simplicity in most previous studies. In multiple target tracking, occlusions will be caused by target size effect, one target can become a moving obstacle blocking the direct channel between the anchor and another target. In this paper, the data association problem in multiple target tracking is investigated. To reduce the computational complexity of traditional Joint Probabilistic Data Association (JPDA) algorithm, a modified JPDA algorithm is proposed to execute data association in multiple target tracking by utilizing the information of occlusion conditions, which is identified by a three-step algorithm. Simulation results show that the proposed algorithm is with good tracking performance and low computational complexity.

Url:
DOI: 10.1109/ICC.2015.7249379

Links to Exploration step

Hal:hal-01246931

Le document en format XML

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<title xml:lang="en">Multiple target tracking under occlusions using modified Joint Probabilistic Data Association</title>
<author role="aut">
<persName>
<forename type="first">Xiufang</forename>
<surname>Shi</surname>
</persName>
<idno type="halAuthorId">1264272</idno>
<orgName ref="#struct-302424"></orgName>
<affiliation ref="#struct-8138"></affiliation>
</author>
<author role="aut">
<persName>
<forename type="first">Ye-Qiong</forename>
<surname>Song</surname>
</persName>
<email>song@loria.fr</email>
<idno type="halAuthorId">64526</idno>
<affiliation ref="#struct-205122"></affiliation>
</author>
<author role="aut">
<persName>
<forename type="first">Zaiyue</forename>
<surname>Yang</surname>
</persName>
<idno type="halAuthorId">1264273</idno>
<orgName ref="#struct-302424"></orgName>
<affiliation ref="#struct-8138"></affiliation>
</author>
<author role="aut">
<persName>
<forename type="first">Jiming</forename>
<surname>Chen</surname>
</persName>
<idno type="halAuthorId">138780</idno>
<affiliation ref="#struct-8138"></affiliation>
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<title level="m">Proceedings of 2015 IEEE International Conference on Communications, ICC 2015.</title>
<meeting>
<title>2015 IEEE International Conference on Communications, ICC 2015</title>
<date type="start">2015-06-08</date>
<date type="end">2015-06-12</date>
<settlement>London</settlement>
<country key="GB">United Kingdom</country>
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<resp>conferenceOrganizer</resp>
<name>IEEE</name>
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<editor>IEEE</editor>
<imprint>
<publisher>IEEE</publisher>
<biblScope unit="serie">Proceedings of 2015 IEEE International Conference on Communications, ICC 2015.</biblScope>
<biblScope unit="pp">6 (pp.6615 - 6620)</biblScope>
<date type="datePub">2015-06-08</date>
</imprint>
</monogr>
<idno type="doi">10.1109/ICC.2015.7249379</idno>
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<language ident="en">English</language>
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<classCode scheme="halDomain" n="info.info-ni">Computer Science [cs]/Networking and Internet Architecture [cs.NI]</classCode>
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<abstract xml:lang="en">The size of target will induce a degradation of tracking performance, which has been neglected for simplicity in most previous studies. In multiple target tracking, occlusions will be caused by target size effect, one target can become a moving obstacle blocking the direct channel between the anchor and another target. In this paper, the data association problem in multiple target tracking is investigated. To reduce the computational complexity of traditional Joint Probabilistic Data Association (JPDA) algorithm, a modified JPDA algorithm is proposed to execute data association in multiple target tracking by utilizing the information of occlusion conditions, which is identified by a three-step algorithm. Simulation results show that the proposed algorithm is with good tracking performance and low computational complexity.</abstract>
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