visual object tracking based on mean-shift and particle-kalman filter视觉物体跟踪基于均值漂移和particle-kalman过滤器

visual object tracking based on mean-shift and particle-kalman filter视觉物体跟踪基于均值漂移和particle-kalman过滤器

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时间:2019-03-16

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1、硕士留学生学位论文VisualObjectTrackingBasedonMean-shiftandParticleandandPPartP-KalmanFilter作者姓名IreneAnindaputriIswanto学科专业ElectricalandComputerEngineering指导教师李彬副教授所在学院AutomationScienceAndEngineering论文提交日期2016年5月23日VisualObjectTrackingBasedonMean-shiftandParticle-KalmanFilterADissertationSubmi

2、ttedfortheDegreeofMasterCandidate:IreneAnindaputriIswantoSupervisor:AssociateProfessorBinLiSouthChinaUniversityofTechnologyGuangzhou,China分类号:学校代号:10561学号:201422800063华南理工大学硕士学位论文VisualObjectTrackingBasedonMean-shiftandParticle-KalmanFilter作者姓名:IreneAnindaputriIswanto指导教师姓名、职称:李彬,副教授

3、申请学位级别:工程硕士学科专业名称:电气与计算机程研究方向:图像处理论文提交日期:2016年05月23日论文答辩日期:2016年06月08日学位授予单位:华南理工大学学位授予日期:2016年06月25日答辩委员会成员:主席:LUGUONENGG委员:裴海龙,苏为洲,李向阳,李彬gABSTRACTDuetotheincreasingofvideosurveillancesystemrequirements,Intelligentvideosurveillancesystemhasbecomechallengingtopicincomputervisionresea

4、rchfield.Therearefourkeystepsinintelligentvideosurveillancesystem,i.e.objectdetection,objectclassification,objecttracking,andobjectanalysis.Amongthesesteps,objecttrackingisconsideredascrucialandsignificanttaskinintelligentvideosurveillancesystem.Objecttrackingisconsideredasdifficultt

5、askbecauseofseveralproblemssuchasilluminationvariation,trackingnon-rigidobject,non-linearmotion,occlusion,andrequirementofrealtimeimplementation.Thereforeitisnecessarytobuildavisualobjecttrackingalgorithmwhichcanovercometheseproblems.Everysinglealgorithminvisualobjecttrackingalwaysha

6、sbothstrengthsanddrawbacks.Therefore,utilizingonlyonesinglealgorithmfortrackingusuallyisconsideredasinefficientbecauseeverysinglealgorithmhaslimitations.Basedonthisreason,inthisthesisatrackingalgorithmwhichcombinesmean-shiftandparticle-Kalmanfilterisproposed.Intheproposedmethod,mean-

7、shiftisusedasmastertrackerwhenthetargetobjectisnotoccluded.Whenocclusionisoccurredorthemean-shifttrackingresultisnotconvincing,particle-Kalmanfilterwillactasmastertrackertoimprovethetrackingresults.Experimentalshowsthattheproposedmethodcanworkwellindealingwithtrackingproblemssuchasno

8、n-rigidobjec

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