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1、FragmentsBasedParametricTrackingPrakashC,BalamanoharPaluri,NalinPradeepS,andHiteshShahSarnoffInnovativeTechnologiesPrivateLimited,Ashaarch,MagrathRoad,Bangalore-560025,IndiaAbstract.Thepaperproposesaparametricapproachforcolorbasedtracking.Themethodfragmen
2、tsamultimodalcolorobjectintomultiplehomogeneous,unimodal,fragments.Thefragmentationprocessconsistsofmultilevelthresholdingoftheobjectcolorspacefollowedbyanas-sembling.Eachhomogeneousregionisthenmodelledusingasinglepara-metricdistributionandthetrackingisa
3、chievedbyfusingtheresultsofthemultipleparametricdistributions.Theadvantageofthemethodliesintrackingcomplexobjectswithpartialocclusionsandvariousdefor-mationslikenon-rigid,orientationandscalechanges.Weevaluatetheperformanceoftheproposedapproachonstandarda
4、ndchallengingrealworlddatasets.1IntroductionTwoprominentcomponentsofatrackingsystemare:objectdescriptorandsearchmechanism.Objectdescriptoristherepresentationoftheobjecttobetrackedusingasetoffeaturesthatcapturevariouspropertiesoftheobjectsuchastheappearan
5、ce,shape,textureetc.Givenanobjectdescriptor,thesearchmechanismlike[1,2],locatestheregioninanewimagethatbestmatchestheobjectdescription.Therearemultiplemethodssuggestedintheliteratureforobjectdescriptors.Mostofthesuccessfulmethodsfortrackingemploynon-para
6、metricobjectde-scriptorlikehistogram[1,3,4,5,6,7],asitfaithfullycapturesthevariabilityinthefeaturesoftheobjecttobetracked.However,withtheincreaseinnumberofobjectstobetrackedorthefeaturestobeconsidered,thehistogramsizegrowsexponentiallywhichisanundesiredb
7、ehavior.Toaddressthisissue,weproposeaparametricobjectdescriptorforcolorbasedtracking.AnN-dimensionalGaussiandistributionisemployedastheobjectdescriptorintheproposedapproach.Suchadescriptorcanaccuratelymodelaunimodalobject.Butobjectsunderconsiderationfort
8、rackingaregenerallymultimodalincolorspacemakingN-dGaussiandescriptorinsufficient.Hence,weneedtoconvertmultimodalobjectstounimodalrepresentation.Primarily,therearetwowaystoachievethisconversion:–Byprojectingthemultimodalobjec
