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1、DecentralizedParticleFilterforJointIndividual-GroupTrackingLorisBazzania;bMarcoCristania;bVittorioMurinoa;baUniversityofVerona,StradaleGrazie,Verona,ItalybPatternAnalysis&ComputerVision,IstitutoItalianodiTecnologia,ViaMorego,Genova,Italyname.surname@itt.itAbstractInthispaper,weaddressthet
2、askoftrackinggroupsofpeopleinsurveillancescenarios.Thisisamajorchallengeincomputervision,sincegroupsarestructuredentities,subjectedtorepeatedsplitandmergeevents.Oursolutionisajointindividual-grouptrackingframework,inspiredbyarecenttechniquedubbeddecentralizedparticlefiltering.Theproposedst
3、rategyfactorizesthejointindividual-groupstatespaceintwodependentsubspaceswhereindividualsandgroupssharetheknowledgeofthejointindividual-Figure1:Grouptrackingresults(coloredconvexhulls)ofgroupdistribution.Inpractice,weestablishatightrelationtheproposedFriendsmeetdataset(firstrow)andofBIWIof
4、mutualsupportbetweenthemodelingofindividualsanddataset(secondrow)[22].thatofgroups,promotingtheideathatgroupsarebettertrackedifindividualsareconsidered,andviceversa.Exten-groupstatespaceintwoconditionallydependentsubspaces,siveexperimentsonapublishedandnoveldatasetvalidatesothatitispossib
5、letomodel1)thesingleindividuals,andourintuition,openinguptomanyfuturedevelopments.2)thegroupsgiventheknowledgeoftheindividuals.WedubbedourproposalasDEEPER-JIGT:DEcentralizEdPar-ticlefiltERforJointIndividual-GroupTracking.1.IntroductionManyinterestingqualitiescanbeascribedtoDEEPER-Grouptrac
6、kingconsistsinfollowingtightformationsofJIGT.Firstofall,theabsenceofheuristicstohandlegroupindividualswhiletheyarewalkingorinteracting(Fig.1).events:theyareallgovernedbyprobabilitydistributionsThisrecentopenchallengeisimportantinmanyrespects:inwhoseparameterscanbelearnedfromtrainingdata.M
7、ore-computervisionandsignalprocessing,itmayhelpinlocat-over,DEEPER-JIGTupdatesthegroupinformationinaningindividualtargetsinthecaseofmissingmeasurementsonlinefashion,wherethetrackinghistoryoftheindividuals[21,22];insurveillance,itmayrevealsocialbondsbetweenisintrinsi
