Optical Engineering 4512, 127201 December 2006 Depth from mo
时间:2025-04-05
时间:2025-04-05
One of the essential problems in computer vision is to recover the distance information of an object from captured images. Its application areas range from industrial inspection and reverse engineering to autonomous robot navigation
OpticalEngineering45 12 ,127201 December2006
Depthfrommotionanddefocusblur
Huei-YungLin,MEMBERSPIEChia-HongChang
NationalChungChengUniversityDepartmentofElectricalEngineering168UniversityRoad
Min-HsiungChia-Yi621,TaiwanE-mail:lin@u.edu.tw
Abstract.Findingthedistanceofanobjectinascenefromintensityimagesisanessentialprobleminmanyapplications.Inthiswork,wepresentanovelmethodfordepthrecoveryfromasinglemotionanddefocusblurredimage.Undertheassumptionofuniformlateralmotionofthecameraduring niteexposuretime,boththepinholemodelandthecamerawitha niteapertureareconsidered.Itisshownthattheimageblurproducedbyuniformlinearmotionofthecameraisinverselyproportionaltothedistanceoftheobject.Furthermore,ifthespeedoftherelativemotionisknown,thedepthoftheobjectcanbeacquiredbyidentifyingtheblurparameters.Animageblurmodelisformulatedbasedongeometricoptics.Theblurextentisestimatedbyintensitypro leanalysisandfocusmeasurementofthedeblurredimages.Theproposedmethodisveri edexperimentallyusingdifferenttypesoftestpatternsinanindoorenvironment.©2006SocietyofPhoto-OpticalInstrumentation
Engineers. DOI:10.1117/1.2403851
Subjectterms:motinblur;defocusblur;depthrecovery.
Paper050643RRreceivedAug.9,2005;revisedmanuscriptreceivedMay27,2006;acceptedforpublicationJun.5,2006;publishedonlineDec.11,2006.
1Introduction
Oneoftheessentialproblemsincomputervisionistore-coverthedistanceinformationofanobjectfromcapturedimages.Itsapplicationareasrangefromindustrialinspec-tionandreverseengineeringtoautonomousrobotnaviga-tionandcomputergraphics.Typically,thevisualcuesob-servedintherecordedimagesareusedfordepthperceptionofthescene.Forexample,the3-Dinformationcanbeen-codedinthetextureorshadinginformationoftheobject,imagedisparityfrommultipleviewpoints,depthof eldoftheoptics,etc.Thisworkaimstoaddresstheproblemofdepthrecoveryusingthevisualcuesprovidedbybothcam-eramotionandopticaldefocus.Speci cally,monlyusedtechniquesfordepthrecoveryincludeshapefromstereoormotion,shapefromshading,shapefromsilhouettes,andphotometricstereo.1Thesemethodsrequireeithermultipleimagescapturedfromdifferentviewpoints,ordifferentilluminationconditionsappliedforthesingleviewpointimageacquisition.Althoughitispos-sibletoachieveexcellent3-Dreconstructionresultsfrommultipleviewpoints,thecomputationalcostisconsiderablyexpensive.Inadditiontogeneraldepthrecoveryalgo-rithms,whichrelyonthechangesoftheenvironmentortheimagingposition,therearealsosomeothertechniquesthatutilizetheactiveadjustmentsoftheinternalcameraparam-eters.Someoftheproposedmethodsincludedepthfromzoominganddepthfromfocus/defocus.Thedepthinforma-tionisextractedbycomparingseveralimagesrecordedbyasinglecamerawithdifferentcameraparametersettings.Amotorizedzoomlensisusuallyrequiredtochangethezoomorfocuspositionsintheseapproaches.
Depthfromdefocusblurisaclassicapproachtorecover
thedistanceofanobjectandsimultaneouslyrestoreafo-cusedimageusingafewout-of-focusimages.2–4Theim-agesareusuallyobtainedfromasingleviewpoint,andthecamerahastoremainstaticduringimageacquisition.Thedepthoftheobjectisthencomputedusingtheamountofdefocusblurassociatedwiththerecordedimage.Recently,defocusimagecuehasalsobeencombinedwithstereotechniquesfordensedepthmaprecovery.Deschênes,Ziou,andFuchs5proposedauni edapproachforacooperativeandsimultaneousestimationofdefocusblurandspatialshiftsfromastereoimagepair.Basedongeneralizedmo-ment,expansion,theyhadformulatedasystemofequationsfordepthcomputation.Rajagopalan,Chadhuri,andMudenagudi6modeledthedepthandthefocusedimageindividuallyasMarkovrandom elds.Theyusedtwode-focusedstereoimagepairstoobtainadensedepthmapaswellasafocusedimageofthescene.
Differentfromopticaldefocus,motionblurisaresultof niteacquisitiontimeofpracticalcamerasandtherelativemotionbetweenthecameraandthescene.Forarapidscenechange,itisnotnegligibleevenwithapinholecam-eramodel.Traditionally,imagedegradationcausedbymo-tionbluristreatedasanundesirableartifactandusuallyhastoberemovedbeforefurtherprocessing.7Recently,motionblurhasbeenusedinvariousapplicationssuchassurveil-lancesystems,8computeranimation,9increasingthespatialresolutionofstillimagesfromvideosequences,10ormea-suringthespeedofamovingvehicle.11Althoughtheresto-rationtechniquesforimagedegradationcausedbymotionblurhavebeeninvestigatedforthepastfewdecades,12–14fairlylittleworkhasbeendonefordepthrecoveryusingmotionblurcues.Someofthepreviousresearchdealingwithcamera orobject motionandopticaldefocuscanbefound,forexample,inRefs.15–17.
ThemostrelevantresearchtothisworkisprobablytheworkgivenbyMylesanddaVitoriaLobo.15Theypre-
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