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基于视觉信息融合的驾驶员疲劳监测方法综述.docx

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基于视觉信息融合的驾驶员疲劳监测方法综述 Introduction Driverfatigueisasignificantcauseofaccidentsontheroad,andtheproblemisbecomingmorewidespreadduetotheincreasingnumberofvehiclesontheroadandlongerdrivinghours.Hence,thedevelopmentoftechniquesandtoolsforeffectivedriverfatiguemonitoringisessentialinensuringroadsafetyandreducingtheriskofaccidents.Oneeffectiveapproachistheintegrationofvisualinformation,whichinvolvescombiningdatafromvariousvisualsensorstorecognizeandmonitorfatigueamongdrivers.Thispaperprovidesacomprehensivereviewofvisualinformationfusiontechniquesfordriverfatiguemonitoring. VisualInformationFusionTechniques Visualinformationfusioninvolvescombiningdatafrommultiplevisualsensors,suchascameras,infraredsensors,anddepthsensors,toprovideamoreaccurate,robust,andcompleterepresentationoftheenvironment.Inthecontextofdriverfatiguemonitoring,visualinformationfusiontechniquesareusedtorecognizeandidentifyfatigue-relatedsymptomsandpatternsbasedonvisualdata.Thefollowingaresomeofthecommontechniquesusedinvisualinformationfusionfordriverfatiguemonitoring: 1.Eye-Tracking Eye-trackinginvolvesusingcamerasorsensorstoobserveandrecordeyemovementsandgazedirection.Thistechniqueisbasedontheprinciplethatwhenapersonisfatigued,theireyelidsaremorelikelytodroop,andtheireyestendtocloselongerandmorefrequently.Eye-trackingdatacanalsobeusedtodetecteyemovements,suchasmicrosaccades,whichareindicativeofdriverattention.Byfusingeye-trackingdatawithothervisualinformation,suchasfacialexpressions,headposition,andposturalchanges,amorerobustandaccuratedriverfatiguemonitoringsystemcanbedeveloped. 2.FacialExpressionAnalysis Facialexpressionanalysisinvolvesanalyzingadriver'sfacialfeatures,suchasthemouth,eyes,andeyebrows,toidentifyspecificexpressionsassociatedwithfatigue.Forinstance,droopingeyelids,mouthgaping,andyawningarecommonexpressionsoffatiguethatcanbedetectedusingfacialexpressionanalysistechniques.Byanalyzingtheintensityandfrequencyoftheseexpressions,adriver'sfatiguelevelcanbeestimated.Facialexpressionanalysiscanbecomb