Multi-object tracking with an adaptive generalize d lab ele d multi-Bernoulli filter
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Do, Cong-Thanh | - |
dc.contributor.author | Nguyen, Tran Thien Dat | - |
dc.contributor.author | Moratuwage, Diluka | - |
dc.contributor.author | Shim, Changbeom | - |
dc.contributor.author | Chung, Yon Dohn | - |
dc.date.accessioned | 2022-05-09T05:42:12Z | - |
dc.date.available | 2022-05-09T05:42:12Z | - |
dc.date.created | 2022-05-09 | - |
dc.date.issued | 2022-07 | - |
dc.identifier.issn | 0165-1684 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/140797 | - |
dc.description.abstract | A B S T R A C T The challenges in multi-object tracking mainly stem from the random variations in the cardinality and states of objects during the tracking process. Further, the information on locations where the objects appear, their detection probabilities, and the statistics of the sensor's false alarms significantly influence the tracking accuracy of the filter. However, this information is usually assumed to be known and provided by the users. In this paper, we propose an adaptive generalized labeled multi-Bernoulli (GLMB) filter which can track multiple objects without prior knowledge of the aforementioned information. Experimental results show that the performance of the proposed filter is comparable to an ideal GLMB filter supplied with correct information of the tracking scenarios.(c) 2022 Elsevier B.V. All rights reserved. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER | - |
dc.subject | RANDOM FINITE SETS | - |
dc.subject | MULTITARGET TRACKING | - |
dc.subject | CELLS | - |
dc.subject | PHD | - |
dc.title | Multi-object tracking with an adaptive generalize d lab ele d multi-Bernoulli filter | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Chung, Yon Dohn | - |
dc.identifier.doi | 10.1016/j.sigpro.2022.108532 | - |
dc.identifier.scopusid | 2-s2.0-85126012764 | - |
dc.identifier.wosid | 000782990000006 | - |
dc.identifier.bibliographicCitation | SIGNAL PROCESSING, v.196 | - |
dc.relation.isPartOf | SIGNAL PROCESSING | - |
dc.citation.title | SIGNAL PROCESSING | - |
dc.citation.volume | 196 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordPlus | RANDOM FINITE SETS | - |
dc.subject.keywordPlus | MULTITARGET TRACKING | - |
dc.subject.keywordPlus | CELLS | - |
dc.subject.keywordPlus | PHD | - |
dc.subject.keywordAuthor | Adaptive birth model | - |
dc.subject.keywordAuthor | Multi-object Bayes filter | - |
dc.subject.keywordAuthor | Bootstrapping | - |
dc.subject.keywordAuthor | GLMB Filter | - |
dc.subject.keywordAuthor | Unknown clutter rate | - |
dc.subject.keywordAuthor | Unknown detection probability | - |
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