Multiple object tracking: A literature review

Cited 312 time in webofscience Cited 0 time in scopus
  • Hit : 250
  • Download : 14
DC FieldValueLanguage
dc.contributor.authorLuo, Wenhanko
dc.contributor.authorXing, Junliangko
dc.contributor.authorMilan, Antonko
dc.contributor.authorKim, Tae-Kyunko
dc.date.accessioned2021-12-03T06:41:03Z-
dc.date.available2021-12-03T06:41:03Z-
dc.date.created2021-11-29-
dc.date.created2021-11-29-
dc.date.created2021-11-29-
dc.date.created2021-11-29-
dc.date.issued2021-04-
dc.identifier.citationARTIFICIAL INTELLIGENCE, v.293, pp.103448-
dc.identifier.issn0004-3702-
dc.identifier.urihttp://hdl.handle.net/10203/289918-
dc.description.abstractMultiple Object Tracking (MOT) has gained increasing attention due to its academic and commercial potential. Although different approaches have been proposed to tackle this problem, it still remains challenging due to factors like abrupt appearance changes and severe object occlusions. In this work, we contribute the first comprehensive and most recent review on this problem. We inspect the recent advances in various aspects and propose some interesting directions for future research. To the best of our knowledge, there has not been any extensive review on this topic in the community. We endeavor to provide a thorough review on the development of this problem in recent decades. The main contributions of this review are fourfold: 1) Key aspects in an MOT system, including formulation, categorization, key principles, evaluation of MOT are discussed; 2) Instead of enumerating individual works, we discuss existing approaches according to various aspects, in each of which methods are divided into different groups and each group is discussed in detail for the principles, advances and drawbacks; 3) We examine experiments of existing publications and summarize results on popular datasets to provide quantitative and comprehensive comparisons. By analyzing the results from different perspectives, we have verified some basic agreements in the field; and 4) We provide a discussion about issues of MOT research, as well as some interesting directions which will become potential research effort in the future.-
dc.languageEnglish-
dc.publisherElsevier BV-
dc.titleMultiple object tracking: A literature review-
dc.typeArticle-
dc.identifier.wosid000621632800004-
dc.identifier.scopusid2-s2.0-85099231725-
dc.type.rimsART-
dc.citation.volume293-
dc.citation.beginningpage103448-
dc.citation.publicationnameARTIFICIAL INTELLIGENCE-
dc.identifier.doi10.1016/j.artint.2020.103448-
dc.embargo.liftdate9999-12-31-
dc.embargo.terms9999-12-31-
dc.contributor.localauthorKim, Tae-Kyun-
dc.contributor.nonIdAuthorLuo, Wenhan-
dc.contributor.nonIdAuthorXing, Junliang-
dc.contributor.nonIdAuthorMilan, Anton-
dc.description.isOpenAccessN-
dc.type.journalArticleReview-
dc.subject.keywordAuthorMulti-object tracking-
dc.subject.keywordAuthorData association-
dc.subject.keywordAuthorSurvey-
dc.subject.keywordPlusMULTITARGET TRACKING-
dc.subject.keywordPlusPERFORMANCE EVALUATION-
dc.subject.keywordPlusMULTIOBJECT TRACKING-
dc.subject.keywordPlusVISUAL SURVEILLANCE-
dc.subject.keywordPlusMODEL-
dc.subject.keywordPlusMOTION-
dc.subject.keywordPlusASSOCIATION-
dc.subject.keywordPlusPROPAGATION-
dc.subject.keywordPlusVEHICLE-
dc.subject.keywordPlusSET-
Appears in Collection
CS-Journal Papers(저널논문)
Files in This Item
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 312 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0