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1、AFASTALGORITHMFORVISION-BASEDHANDGESTURERECOGNITIONFORROBOTCONTROLAsanterabiMalima,ErolOzgur,andMu~jdat(7etinFacultyofEngineeringandNaturalSciences,SabanciUniversity,Tuzla,Istanbul,Turkeyma1ima@su.sabanciuniv.edu,ero1@su.sabanciuniv.edu,andmcetin@sabanciuniv.eduAbstractprincipalcomponentanalysi
2、s[6],Fourierdescriptors,neuralnetworks,orientationhistograms[7],andparticlefilters[8].WeproposeafastalgorithmforautomaticallyrecognizingalimitedsetofgesturesfromhandimagesforOurfocustherecognitionofafixedsetofmanualarobotcontrolapplication.Handgesturerecognitionisacommandsbyarobot,inareasonably
3、structuredenvironmentchallengingprobleminitsgeneralform.Weconsiderainrealtime.Thereforethespeed,hencesimplicityofthefixedsetofmanualcommandsandareasonablystructuredalgorithmisimportant.Wedevelopandimplementsuchaenvironment,anddevelopasimple,yeteffective,procedureinthiswork.Ourapproachinvolvesse
4、gmentingtheprocedureforgesturerecognition.Ourapproachcontainshandbasedonskincolorstatistics,aswellassizeconstraints.stepsforsegmentingthehandregion,locatingthefingers,Wethenfindthecenterofgravity(COG)ofthehandregionandfinallyclassifyingthegesture.ThealgorithmisaswellthefarthestpointfromtheCOG.B
5、asedonthesepre-invarianttotranslation,rotation,andscaleofthehand.processingsteps,wederiveasignalthatcarriesinformationonWedemonstratetheeffectivenessofthetechniqueonrealtheactivityofthefingersinthesign.Finallyweidentifytheimagery.signbasedonthatsignal.Ouralgorithmisinvarianttorotations,translat
6、ionsandscaleofthehand.Furthermore,thetechniquedoesnotrequirethestorageofahandgesture1.Introductiondatabaseintherobot'smemory.Wedemonstratetheeffectivenessofourapproachonrealimagesofhandgestures.Vision-basedautomatichandgesturerecognitionhasbeenaveryactiveresearchtopicinrecentyearswithmotivating
7、applicationssuchashumancomputerinteraction(HCI),robot2.HandGestureRecognitioncontrol,andsignlanguageinterpretation.ThegeneralproblemisquitechallengingdueanumberofissuesincludingtheConsiderarobotnavigationproblem,inwhicharobotcompl
