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基于DSP的通过局部特征实时物体识别嵌入式系统x.docx

基于DSP的通过局部特征实时物体识别嵌入式系统x.docx

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附录A

Real-timeobjectrecognitionusinglocalfeaturesonaDSP-basedembeddedsystem

Abstract

Inthelastfewyears,objectrecognitionhasbecomeoneofthemostpopulartasksincomputervision.Inparticular,thiswasdrivenbythedevelopmentofnewpowerfulalgorithmsforlocalappearancebasedobjectrecognition.So-called‘‘smartcameras’’withenoughpowerfordecentralizedimageprocessingbecamemoreandmorepopularforallkindsoftasks,especiallyinthefieldofsurveillance.Recognitionisaveryimportanttoolastherobustrecognitionofsuspiciousvehicles,personsorobjectsisamatterofpublicsafety.Thissimplymakesthedeploymentofrecognitioncapabilitiesonembeddedplatformsnecessary.Inourworkweinvestigatethetaskofobjectrecognitionbasedonstate-of-the-artalgorithmsinthecontextofaDSP-basedembeddedsystem.Weimplementseveralpowerfulalgorithmsforobjectrecognition,namelyaninterestpointdetectortogetherwithanregiondescriptor,andbuildamedium-sizedobjectdatabasebasedonavocabularytree,whichissuitableforourdedicatedhardwaresetup.Wecarefullyinvestigatetheparametersofthealgorithmwithrespecttotheperformanceontheembeddedplatform.Weshowthatstate-of-the-artobjectrecognitionalgorithmscanbesuccessfullydeployedonnowadayssmartcameras,evenwithstrictlylimitedcomputationalandmemoryresources.

Keywords DSP;Objectrecognition;Localfeatures;Vocabularytree

Introduction

Objectrecognitionisoneofthemostpopulartasksinthefieldofcomputervision.Inthepastdecade,bigeffortsweremadetobuildrobustobjectrecognitionsystemsbasedonappearancefeatureswithlocalextent.Forsuchaframeworktobeapplicableintherealworldseveralattributesareveryimportant:insensitivityagainstrotation,illuminationorviewpointchanges,aswellasreal-timebehaviorandlarge-scaleoperation.Currentsystemsalreadyhavealotofthesepropertiesand,

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