Multiple target tracking under occlusions using modified Joint Probabilistic Data Association
Identifieur interne : 000502 ( Main/Exploration ); précédent : 000501; suivant : 000503Multiple target tracking under occlusions using modified Joint Probabilistic Data Association
Auteurs : Xiufang Shi [République populaire de Chine] ; Ye-Qiong Song [France] ; Zaiyue Yang [République populaire de Chine] ; Jiming Chen [République populaire de Chine]Source :
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
Affiliations:
- France, République populaire de Chine
- Grand Est, Lorraine (région)
- Metz, Nancy
- Université de Lorraine
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Le document en format XML
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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.</div></front></TEI><affiliations><list><country><li>France</li><li>République populaire de Chine</li></country><region><li>Grand Est</li><li>Lorraine (région)</li></region><settlement><li>Metz</li><li>Nancy</li></settlement><orgName><li>Université de Lorraine</li></orgName></list><tree><country name="République populaire de Chine"><noRegion><name sortKey="Shi, Xiufang" sort="Shi, Xiufang" uniqKey="Shi X" first="Xiufang" last="Shi">Xiufang Shi</name></noRegion><name sortKey="Chen, Jiming" sort="Chen, Jiming" uniqKey="Chen J" first="Jiming" last="Chen">Jiming Chen</name><name sortKey="Yang, Zaiyue" sort="Yang, Zaiyue" uniqKey="Yang Z" first="Zaiyue" last="Yang">Zaiyue Yang</name></country><country name="France"><region name="Grand Est"><name sortKey="Song, Ye Qiong" sort="Song, Ye Qiong" uniqKey="Song Y" first="Ye-Qiong" last="Song">Ye-Qiong Song</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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