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基于多特征融合的视频关键帧提取的若干问题研究.docx

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基于多特征融合的视频关键帧提取的若干问题研究 Abstract Videokeyframeextractionisachallengingprobleminthefieldofcomputervisionandmultimediaanalysis.Thispaperproposesamulti-featurefusionapproachtotacklethekeyframeextractionproblem.Specifically,weexploretheuseofcolorhistogram,motionvectors,andsaliencymapascomplementaryfeaturestobetterrepresentthekeyframes.Experimentalresultsshowthatourapproachoutperformstheexistingkeyframeextractionmethodsonseveralbenchmarkdatasets.Moreover,weanalyzetheimpactofdifferentfeaturecombinationsandfusionmethodsontheperformanceofthesystem. Introduction Withtheexplosivegrowthofmultimediadata,videoshavebecomeoneofthemostpopularformatsofcontentinthedigitalera.However,thelargesizeofvideodatasetshasmadevideoanalysisandindexingchallengingtasks.Oneoftheimportantstepsinvideoprocessingandanalysisiskeyframeextraction,whichaimstoidentifythemostinformativeandrepresentativeframesinavideosequence.Keyframescanbeusedforvideosummarization,indexing,andretrieval,amongothers. Severalapproacheshavebeenproposedforkeyframeextraction,includingthreshold-basedmethods,clustering-basedmethods,andmachinelearning-basedmethods.However,thesemethodsoftenrelyonasingletypeoffeature,whichmaynotcapturealltherelevantinformationinthevideo.Inrecentyears,multi-featurefusionapproacheshaveemergedasapromisingsolutiontoovercomethislimitation.Byusingmultiplefeatures,thesemethodscanbettercapturethevisualandsemanticcontentofthevideo. Thispaperproposesamulti-featurefusionapproachforvideokeyframeextraction.Specifically,weexploretheuseofcolorhistogram,motionvectors,andsaliencymapascomplementaryfeaturestorepresentthekeyframes.Therestofthepaperisorganizedasfollows.InSection2,wereviewtherelatedworkonvideokeyframeextraction.InSection3,wedescribeindetailourproposedmulti-featurefusionapproach.InSection4,wepresenttheexperimentalresultsandanalysis.Finally,weconcludethepaperinSection5. RelatedWork Theproblemofvideokeyframeextractionhasbeenextensivelystudiedintheliterature.Earlyapproacheswerebasedonthresholdingtechniques,whic