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1、AKnowledge-BasedObjectsTrackingAlgorithminColorVideoUsingKalmanFilterApproachA.H.MazinanA.Amir-LatifiM.F.KazemiElectricalEngineeringDepartment,ElectricalEngineeringDepartment,ElectricalEngineeringDepartment,IslamicAzadUniversity(IAU),IslamicAzadUniversity(IAU),IslamicAzadUniver
2、sity(IAU),SouthTehranBranchSouthTehranBranchLahijanBranchTehran,IranTehran,IranLahijan,Irane-mail:mazinan@azad.ac.ire-mail:arash_amirlatifi@yahoo.come-mail:mfkazemi@iau-lahijan.ac.irAbstract—Anewknowledge-basedalgorithmforthepurposeKalmanfilterapproachestimatesthestateofadynami
3、cofrigidandnon-rigidobjectstrackingthroughcolorfeatureinsystem,evenifthesystemisaccuratelyunknown[1]-[11].videosequencesisproposedinthisresearch.ThemeanshiftThispaperisorganizedasfollows.TheMStracking(MS)algorithm,astheefficientmethodintheareaofcolor-algorithmispresentedinSecti
4、onII.Theproposedtrackingbasedobjectstracking,isimprovedtosolvethetrackingalgorithmisgiveninSectionIIIandfinallytheexperimentalproblems,suchasbackgroundwithsimilarcolors,partialorresultsandconcludingremarkarepresentedinSectionsIVfullocclusion,sensibly,andsoon.Inthealgorithmprese
5、ntedandV,respectively.here,animprovedconvexkernelfunctionisrealizedtopresentaparticularsolution,sincearobustestimator,i.e.,Kalmanfilterapproachiscorrespondinglyrealized.ExperimentalII.THEMSTRACKINGALGORITHMresultsverifythattheproposedalgorithmisefficient,underseverconditions,wh
6、ilethespeedoftheobjectcouldbeconstant.TheprincipleoftheMStrackingalgorithmisbrieflyconsideredherebythefollowingsteps:Keywords-Kalmanfilterapproach;colorfeature;rigidandnon-rigidobjects;Bhattacharyyacoefficient.1.Calculatingtheprobabilityofthecoloru,intheobjectmodel,bythefollowi
7、ngI.INTRODUCTIONݍො୳ൌC݇ሺԡݔכԡଶሻߜሾܾሺݔכሻെݑሿሺ1ሻRecently,objectstrackingisaconsiderabletopicforୀଵresearchers,intheareaofreal-timeapplications,suchaswheretheinsidepixelslocationofthechosenrectanglessurveillanceandmonitoring.Anefficienttrackingalgorithmככshouldbeabletoimplementins
8、omanydifficultsituations.arepresentedasሼݔ(b,…ଵୀሽݔሻ
