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基于多标签的自动人脸年龄估计分析-analysis of automatic face age estimation based on multiple tags
AbstractAgeestimationisanovelandsignificantresearchdirectionintheareaofbiometricidentification,andthereisplentyofageconcernedinformationcontainedinfacialimages.However,becauseofthedifficultiesingettingenoughtrainingsamplesaswellasthespecialcharacteristicsofagingprocess,theestimationresultsbasedonfacialimagesstillneedtobeimproved.Asaresult,motivatedbytheslowandcontinuousagingprocess,multi-labelbasedmodel,whichisfitterforagingcharacteristics,isintroducedtorepresentthefacialimagesinageestimation.Inmostofthepreviouswork,ageestimationisgenerallyformulatedasasingle-labelbasedproblem.However,sinceagingisagradualprocessandpeoplearealwaysintransitionperiodbetweenages,labelingafacialexamplewithanexactageisadifficultproblem.Meanwhile,sufficienttrainingdataislackformanyages.Inthispaper,toimprovetheaccuracyofageestimation,anovelapproachbyapplyingMulti-LabelLearningtotheagefeaturesisproposed.Inthatapproach,eachfacialimageistreatedasanexampleassociatedwiththeoriginlabelaswellasitsneighboringages,whichmakesthedatamorereliableandsufficient.Themotivationcomesfromtheobservationthat,withagechangesslowlyandsmoothly,peoplewouldlookquitelikethemselvesbeforeandafterseveralyears.Andinthispaper,inordertocapturecomprehensiveinformationinfacialimagesandfurtherbetterthepreviousapproach,multi-instancemodelisalsointroducedintherepresentationoffacialimages.Experimentsshowthattheproposedmulti-labelapproachoutperformsthetraditionalageestimationapproaches.Thoughthemulti-instanceimprovementdoesntachievebetterresults,analysisaswellasthefutureworkisshowninthispaper.Keywords:AgeEstimation,Multi-LabelLearning,Multi-InstanceMulti-LabelLearning目录摘要...............................................................................................................IAbstract............................................................................................................II1绪论1.1研究的背景及意义...............................................................................(1)1.2国内外研究现状..............................
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