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1、34IEEETRANSACTIONSONPATTERNANALYSISANDMACHINEINTELLIGENCE,VOL.24,NO.1,JANUARY2002DetectingFacesinImages:ASurveyMing-HsuanYang,Member,IEEE,DavidJ.Kriegman,SeniorMember,IEEE,andNarendraAhuja,Fellow,IEEEAbstract—Imagescontainingfacesareessentialtointelligentvision-basedhumanc
2、omputerinteraction,andresearcheffortsinfaceprocessingincludefacerecognition,facetracking,poseestimation,andexpressionrecognition.However,manyreportedmethodsassumethatthefacesinanimageoranimagesequencehavebeenidentifiedandlocalized.Tobuildfullyautomatedsystemsthatanalyzethe
3、informationcontainedinfaceimages,robustandefficientfacedetectionalgorithmsarerequired.Givenasingleimage,thegoaloffacedetectionistoidentifyallimageregionswhichcontainafaceregardlessofitsthree-dimensionalposition,orientation,andlightingconditions.Suchaproblemischallengingbec
4、ausefacesarenonrigidandhaveahighdegreeofvariabilityinsize,shape,color,andtexture.Numeroustechniqueshavebeendevelopedtodetectfacesinasingleimage,andthepurposeofthispaperistocategorizeandevaluatethesealgorithms.Wealsodiscussrelevantissuessuchasdatacollection,evaluationmetric
5、s,andbenchmarking.Afteranalyzingthesealgorithmsandidentifyingtheirlimitations,weconcludewithseveralpromisingdirectionsforfutureresearch.IndexTerms—Facedetection,facerecognition,objectrecognition,view-basedrecognition,statisticalpatternrecognition,machinelearning.æ1INTRODUC
6、TIONWITHtheubiquityofnewinformationtechnologyandWenowgiveadefinitionoffacedetection:Givenanmedia,moreeffectiveandfriendlymethodsforarbitraryimage,thegoaloffacedetectionistodeterminehumancomputerinteraction(HCI)arebeingdevelopedwhetherornotthereareanyfacesintheimageand,ifwh
7、ichdonotrelyontraditionaldevicessuchaskeyboards,present,returntheimagelocationandextentofeachface.mice,anddisplays.Furthermore,theeverdecreasingprice/Thechallengesassociatedwithfacedetectioncanbeperformanceratioofcomputingcoupledwithrecentattributedtothefollowingfactors:de
8、creasesinvideoimageacquisitioncostimplythatcomputervisionsystemscanbedeployedindesktopand
