基于低秩-稀疏联合表示的视频序列运动目标检测（英文）.docx

基于低秩-稀疏联合表示的视频序列运动目标检测（英文）
Title:MotionDetectioninVideoSequencesBasedonLow-RankandSparseJointRepresentation
Abstract:
Videomotiondetectionisanessentialtaskincomputervisionapplications,suchasvideosurveillance,videoanalysis,andautonomousdriving.Thispaperproposesanovelapproachformotiondetectioninvideosequencesusingalow-rankandsparsejointrepresentation.Theapproachcombinestheadvantagesofsparserepresentationandlow-rankrepresentationtoeffectivelydetectmovingobjectswhilesuppressingbackgroundnoiseandmaintainingrobustnessagainstvariouschallengingconditions.
1.Introduction
Videomotiondetectionplaysavitalroleinmanyreal-worldapplications,allowingfortheidentificationandtrackingofmovingobjects.Traditionalmotiondetectionmethodsoftensufferfromissuessuchashighcomputationalcomplexity,backgroundclutter,andsensitivitytoilluminationchanges.Therefore,thereisaneedformoreadvancedtechniquesthatcanovercomethesechallengesandachieveaccurateandrobustmotiondetection.
2.RelatedWork
Thissectionprovidesanoverviewofexistingmotiondetectionmethods.Itdiscussesbothtraditionaltechniques,suchasframedifferencingandbackgroundsubtraction,aswellasmorerecentapproachesbasedonsparserepresentationandlow-rankrepresentation.Byanalyzingthelimitationsofthesemethods,themotivationforourproposedapproachisestablished.
3.Methodology
Ourproposedapproachformotiondetectioninvideosequencesisbasedonalow-rankandsparsejointrepresentation.Thekeystepsofthemethodareasfollows:
-VideoPreprocessing:Thevideosequenceispreprocessedtoremovenoiseandenhancethemotioninformation.
-Low-RankRepresentation:Thevideoframesaredecomposedintolow-rankandsparsecomponentsusingrobustlow-rankmatrixfactorizationtechniques.Thelow-rankcomponentrepresentsthebackground,whilethesparsecomponentcapturesthemovingobjects.
-MotionSalientMap:Amotionsalientmapisgeneratedbyconsideringthesparsitylevelandthereconstructedvideoframes.Thismaphighlightstheregionswithsignificantmotion.
-ObjectDetectionandTracking:Finally,objectdetectionandtrackingalgorithmsareappliedtothemotio