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1、TRANSPORTATIONRESEARCHPARTCTransportationResearchPartC6(1998)271±288Areal-timecomputervisionsystemforvehicletrackingandtracsurveillanceBenjaminCoifmana,*,DavidBeymerb,1,PhilipMcLauchlanb,2,JitendraMalikb,3aInstituteofTransportationStudies,UniversityofCaliforn
2、ia,Berkeley,CA,94720,USAbDepartmentofElectricalEngineeringandComputerSciences,UniversityofCalifornia,Berkeley,CA94720-1776,USAReceived30March1998;receivedinrevisedform3December1998;accepted3December1998AbstractIncreasingcongestiononfreewaysandproblemsassociat
3、edwithexistingdetectorshavespawnedaninterestinnewvehicledetectiontechnologiessuchasvideoimageprocessing.Existingcommercialimageprocessingsystemsworkwellinfree-¯owingtrac,butthesystemshavedicultieswithcongestion,sha-dowsandlightingtransitions.Theseproblemsstem
4、fromvehiclespartiallyoccludingoneanotherandthefactthatvehiclesappeardierentlyundervariouslightingconditions.Wearedevelopingafeature-basedtrackingsystemfordetectingvehiclesunderthesechallengingconditions.Insteadoftrackingentirevehi-cles,vehiclefeaturesaretrack
5、edtomakethesystemrobusttopartialocclusion.Thesystemisfullyfunc-tionalunderchanginglightingconditionsbecausethemostsalientfeaturesatthegivenmomentaretracked.Afterthefeaturesexitthetrackingregion,theyaregroupedintodiscretevehiclesusingacommonmotionconstraint.Th
6、egroupsrepresentindividualvehicletrajectorieswhichcanbeusedtomeasuretra-ditionaltracparametersaswellasnewmetricssuitableforimprovedautomatedsurveillance.Thispaperdescribestheissuesassociatedwithfeaturebasedtracking,presentsthereal-timeimplementationofaprototy
7、pesystem,andtheperformanceofthesystemonalargedataset.#1999ElsevierScienceLtd.Allrightsreserved.Keywords:Tracsurveillance;Wide-areadetection;Vehicletracking;Videoimageprocessing;Machinevision*Correspondingauthor.Tel.:+1-510-845-5121;fax:+1-510-642-1246;e-mail:
8、zephyr@eecs.berkeley.edu1D.BeymerisnowwithSRIInternational,333RavenswoodAve,MenloPark,Ca94025.E-mail:beymer@-ai.sri.com2P.McLauchlanisnowwiththeUniversityofSurrey,SchoolofEE,ITandMath.,Gu
