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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/54445
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dc.contributor.authorIhnatsyeva, I.-
dc.contributor.authorBohush, R.-
dc.coverage.spatialМинскen_US
dc.date.accessioned2024-03-01T07:32:48Z-
dc.date.available2024-03-01T07:32:48Z-
dc.date.issued2023-
dc.identifier.citationIhnatsyeva, I. Person re-identification using compound descriptor and invisible region replacement / I. Ihnatsyeva, R. Bohush // Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023) : Proceedings of the 16th International Conference, October 17–19, 2023, Minsk, Belarus / United Institute of Informatics Problems of the National Academy of Sciences of Belarus. – Minsk, 2023. – P. 193–196.en_US
dc.identifier.urihttps://libeldoc.bsuir.by/handle/123456789/54445-
dc.description.abstractIn this paper we proposed person re-identification algorithm using compound descriptor that includes global and local features for the top, middle, and bottom of the person figure. Local areas are formed based on the person figure key points coordinates. If there are not enough visible points, the area is recognized as invisible and feature vector corresponding component is replaced by an average value for the k-nearest neighbors. Testing was performed on datasets for re- identification Market-1501, DukeMTMC-ReID, MSMT17, PolReID1077. Our algorithm allows us to increase accuracy re- identification for metric Rank1 by 8 - 51% and for metric mAP by 28 - 97% relative to the baseline.en_US
dc.language.isoenen_US
dc.publisherBSUen_US
dc.subjectматериалы конференцийen_US
dc.subjectconvolution neuron networksen_US
dc.subjectPolReID1077en_US
dc.subjectocclusionen_US
dc.titlePerson re-identification using compound descriptor and invisible region replacementen_US
dc.typeArticleen_US
Appears in Collections:Pattern Recognition and Information Processing (PRIP'2023) = Распознавание образов и обработка информации (2023)

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