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视频序列中的运动目标检测与跟踪.docx

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视频序列中的运动目标检测与跟踪 Abstract Motiondetectionandtrackingoftargetsinvideosequencesareessentialtasksinmanyapplications,includingsurveillance,robotics,andautonomousdriving.Thispaperinvestigatesdifferenttechniquesformotiondetectionandtrackingofmovingobjectsinvideosequences.Severalmethodsarereviewed,rangingfromtraditionalmethods,suchasbackgroundsubtraction,tomorerecentdeeplearning-basedapproaches.Thepaperexplorestheadvantagesanddisadvantagesofeachmethodandcomparestheirperformanceondifferentdatasets.Finally,thepaperaddressessomeofthechallengesinmotiondetectionandtrackingandproposessomefutureresearchdirections. Introduction Motiondetectionandtrackingoftargetsinvideosequencesarefundamentaltasksincomputervisionandvideoprocessing.Thesetasksincludedetectingmovingobjectsinascene,segmentingtheobjectsfromthebackground,andtrackingtheirmotionsovertime.Thesetasksarecrucialinmanyapplications,suchassurveillance,robotics,andautonomousdriving.Forexample,theycanbeusedinsurveillanceapplicationstodetectandtrackintrudersorsuspiciousactivitiesandinroboticsapplicationstodetectandtrackmovingobjectsinarobot'senvironment. Therearevarioustechniquesformotiondetectionandtracking,rangingfromtraditionalmethods,suchasbackgroundsubtractionandopticalflow,tomorerecentdeeplearning-basedapproaches.Eachmethodhasitsadvantagesanddisadvantages,andthechoiceofmethoddependsonvariousfactors,suchasthecomplexityofthescene,theaccuracyrequired,thecomputationalresourcesavailable,andthequalityofthevideosequence. Thepaperprovidesanoverviewofvariousmethodsformotiondetectionandtrackinginvideosequences.Section2reviewstraditionalmethods,includingbackgroundsubtractionandopticalflow.Section3exploresmorerecentdeeplearning-basedapproaches.Section4comparestheperformanceofdifferentmethodsondifferentdatasets.Section5discussessomeofthechallengesinmotiondetectionandtrackingandproposessomefutureresearchdirections.Finally,Section6summarizesthepaperandprovidessomeconcludingremarks. TraditionalMethods BackgroundSubtraction Backgroundsubtracti