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1、MachineVisionandApplications(2011)22:927945DOI10.1007/s00138-010-0287-7ORIGINALPAPERRoadenvironmentmodelingusingrobustperspectiveanalysisandrecursiveBayesiansegmentationMarcosNieto·JonArróspideLaborda·LuisSalgadoReceived:21July2009/Revised:8April2010/Accepted:5July2010/Publishedonline:8August2010©S
2、pringer-Verlag2010AbstractRecently,vision-basedadvanceddriver-assistanceresearchcentersandusers)duetotheirabilitytoprovidesystems(ADAS)havereceivedanewincreasedinteresttousefulinformationaboutthevehicleenvironmentbyfunc-enhancedrivingsafety.Inparticular,duetoitshighperfor-tioningassensorsforservice
3、ssuchaslanedeparturewarning,mancecostratio,mono-camerasystemsarearisingasthecollisionavoidance,stop-and-go,etc.Inparticular,thesolu-mainfocusofthisfieldofwork.Inthispaperwepresentationsbasedonvideoprocessinghaveplayedanimportantnovelon-boardroadmodelingandvehicledetectionsystem,roleinthisfieldsinceth
4、epastdecade,duetotheirlowcost,whichisapartoftheresultoftheEuropeanI-WAYproject.theincreasedperformanceofmicroprocessorsystems,andThesystemreliesonarobustestimationoftheperspectivetheresearchadvancesinthefieldofcomputervision[1].ofthescene,whichadaptstothedynamicsofthevehicleTheon-boardscenarioposesa
5、numberofchallengesforandgeneratesastabilizedrectifiedimageoftheroadplane.visionsystems,asitisanextremelyvariedenvironment[2].ThisrectifiedplaneisusedbyarecursiveBayesianclassi-Forinstance,itinvolvessuddenandsignificantilluminationfier,whichclassifiespixelsasbelongingtodifferentclasseschanges(aswhenente
6、ringintotunnels),differenttypesofcorrespondingtotheelementsofinterestofthescenario.roadpavement,ortheappearanceoflanemarkings,whichThisstageworksasanintermediatelayerthatisolatessub-mayhavecontraststhatvarysignificantlyfromoneroadtosequentmodulessinceitabsorbstheinherentvariabilityofanother.Moreove
7、r,weatherconditionsmayalsoaffectvisionthescene.Thesystemhasbeentestedon-road,indifferentsystems.Forexample,theimagecouldcontainraindrops,scenarios,includingvariedilluminationandadverseweathermovingwipers,et