AFJPDA: a multiclass multi-object tracking with appearance feature-aided joint probabilistic data association

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dc.contributor.authorKim, Sukkeun
dc.contributor.authorPetrunin, Ivan
dc.contributor.authorShin, Hyo-Sang
dc.date.accessioned2024-03-14T14:14:47Z
dc.date.available2024-03-14T14:14:47Z
dc.date.issued2024-01-02
dc.description.abstractThis study addresses a multiclass multi-object tracking problem in consideration of clutters in the environment. To alleviate issues with clutters, we propose the appearance feature-aided joint probabilistic data association filter. We also implemented simple adaptive gating logic for the computational efficiency and track maintenance logic, which can save the lost track for re-association after occlusion or missed detection. The performance of the proposed algorithm was evaluated against a state-of-the-art multi-object tracking algorithm using both multiclass multi-object simulation and real-world aerial images. The evaluation results indicate significant performance improvement of the proposed method against the benchmark state-of-the-art algorithm, especially in terms of reduction in identity switches and fragmentation.en_UK
dc.description.sponsorshipThis research was supported by the UK Research and Innovation-funded project HADO: project number 10024815en_UK
dc.identifier.citationKim S, Petrunin I, Shin HS. (2024) AFJPDA: a multiclass multi-object tracking with appearance feature-aided joint probabilistic data association. Journal of Aerospace Information Systems, Volume 21, Issue 4, April 2024, pp. 294-304en_UK
dc.identifier.eissn2327-3097
dc.identifier.urihttps://doi.org/10.2514/1.I011301
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/20997
dc.language.isoenen_UK
dc.publisherAIAAen_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectUnmanned Aerial Vehicleen_UK
dc.subjectKalman Filteren_UK
dc.subjectImage Sensoren_UK
dc.subjectMulti-Object Trackingen_UK
dc.subjectJoint Probabilistic Data Associationen_UK
dc.titleAFJPDA: a multiclass multi-object tracking with appearance feature-aided joint probabilistic data associationen_UK
dc.typeArticleen_UK
dcterms.dateAccepted2023-10-24

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