基于DSP的通过局部特征实时物体识别嵌入式系统x文档格式.docx

基于DSP的通过局部特征实时物体识别嵌入式系统x文档格式.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@#@1.Introduction@#@Objectrecognitionisoneofthemostpopulartasksinthefieldofcomputervision.Inthepastdecade,bigeffortsweremadetobuildrobustobjectrecognitionsystemsbasedonappearancefeatureswithlocalextent.Forsuchaframeworktobeapplicableintherealworldseveralattributesareveryimportant:

@#@insensitivityagainstrotation,illuminationorviewpointchanges,aswellasreal-timebehaviorandlarge-scaleoperation.Currentsystemsalreadyhavealotofthesepropertiesand,thoughnotallproblemshavebeensolvedyet,nowadaystheybecomemoreandmoreattractivetotheindustryforinclusioninproductsforthecustomermarket.@#@Inturn,recentlyembeddedvisionplatformssuchassmartcamerashavesuccessfullyemerged,however,onlyofferingalimitedamountofcomputationalandmemoryresources.Nevertheless,embeddedvisionsystemsarealreadypresentinoureverydaylife.Almosteveryone’smobilephoneisequippedwithacameraand,thus,canbetreatedasasmallembeddedvisionsystem.Clearlythisgivesrisetonewapplications,likenavigationtoolsforvisuallyimpairedpersons,orcollaborativepublicmonitoringusingmillionsofartificialeyes.Inaddition,thelowpriceofdigitalsensorsandtheincreasedneedforsecurityinpublicplaceshasledtoatremendousgrowthinthenumberofcamerasmountedforsurveillancepurposes.Theyhavetobesmallinsizeandhavetoprocessthehugeamountsofavailabledataonsite.Furthermore,theyhavetoperformdedicatedoperationsautomaticallyandwithouthumaninteraction.Notonlyinthefieldofsurveillance,butalsointheareasofhouseholdrobotics,entertainment,militaryandindustrialrobotics,embeddedcomputervisionplatformsarebecomingmoreandmorepopularduetotheirrobustnessagainstenvironmentaladversities.EspeciallyDSP-basedembeddedplatformsareverypopularastheyarepowerfulandcheapCPUs,whicharestillsmallinsizeandefficientintermsofpowerconsumption.AsDSPofferthemaximuminflexibilityofthesoftwaretoberun,comparedtootherembeddedunitslikeFPGAs,ASICorGPU,theircurrentsuccessisnotsurprising.@#@Forthereasonsalreadymentioned,recognitiontasksareaveryimportantareaofresearch.However,inthisrespectsomeattributesofembeddedplatformsstrictlylimitthepracticabilityofcurrentstate-of-the-artapproaches.Forexample,theamountofmemoryavailableonadevicestrictlylimitsthenumberofobjectsinthedatabase.Therefore,forbuildinganembeddedobjectrecognitionsystem,onegoalistomaketheamountofdatatorepresentasingleobjectassmallaspossibleinordertomaximizethenumberofrecognizableobjects.Anotherimportantaspectisthereal-timecapabilityofthesesystems.Algorithmshavetobefastenoughtobeoperationalintherealworld.Theyhavetoberobustanduser-friendly;@#@otherwise,aproductequippedwithsuchfunctionalityissimplyunattractivetoapotentialcustomer.Forexample,inaninteractivetourthroughamuseum,objectrecognitiononamobiledevicehastobefastenoughtoallowforcontinuityinguidance.Formallyspeaking,weconsiderthistobeanapplicationrequiringsoftreal-timesystembehavior.Clearly,thisisjustoneexample,andtheexactmeaningofthetermreal-timeisdependentontheconcreteapplication.Westillconsideranobjectrecognitionsystemasbeingreal-@#@timecapable,ifitisablet