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Set-label modeling and deep metric learning on person re-identification
Hao Liu; Bingpeng Ma; Lei Qin; Junbiao Pang; Chunjie Zhang; Qingming Huang
Source PublicationNeurocomputing
2015
Issue151Pages:1283–1292
AbstractPerson re-identification aimsatmatchingindividualsacrossmultiplenon-overlappingadjacentcameras.
By condensingmultiplegalleryimagesofapersonasawhole,weproposeanovelmethodnamedSet-
Label Model(SLM)toimprovetheperformanceofpersonre-identification underthemulti-shotsetting.
Moreover,weutilizemutual-informationtomeasuretherelevancebetweenqueryimageandgallery
sets. Todecreasethecomputationalcomplexity,weapplyaNaive–BayesNearest-Neighboralgorithmto
approximatethemutual-informationvalue.Toovercomethelimitationsoftraditionallinearmetric
learning, wefurtherdevelopadeepnon-linearmetriclearning(DeepML)approachbasedonNeighbor-
hood ComponentAnalysisandDeepBeliefNetwork.Toevaluatetheeffectivenessofourproposed
approaches, SLMandDeepML,wehavecarriedoutextensiveexperimentsontwochallengingdatasetsi-
LIDS andETHZ.Theexperimentalresultsdemonstratethattheproposedmethodscanobtainbetter
performances comparedwiththestate-of-the-artmethods.
KeywordPerson Re-identification Mutual-information Metric Learning Deep Learning Neighborhoodcomponentanalysis
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/15394
Collection类脑智能研究中心
Recommended Citation
GB/T 7714
Hao Liu,Bingpeng Ma,Lei Qin,et al. Set-label modeling and deep metric learning on person re-identification[J]. Neurocomputing,2015(151):1283–1292.
APA Hao Liu,Bingpeng Ma,Lei Qin,Junbiao Pang,Chunjie Zhang,&Qingming Huang.(2015).Set-label modeling and deep metric learning on person re-identification.Neurocomputing(151),1283–1292.
MLA Hao Liu,et al."Set-label modeling and deep metric learning on person re-identification".Neurocomputing .151(2015):1283–1292.
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