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1、RobertCollinsCSE486,PennStateLecture7:CorrespondenceMatchingReading:T&VSection7.2RobertCollinsCSE486,PennStateRecall:DerivativeofGaussianFilterI=dI(x,y)/dxxGxI(x,y)convolveGyI=dI(x,y)/dyyconvolveRobertCollinsCSE486,PennStateObserveandGeneralizeDerivativeofGaussianLookslikevertic
2、alandhorizontalstepedgesKeyidea:Convolution(andcrosscorrelation)withafiltercanbeviewedascomparingalittle“picture”ofwhatyouwanttofindagainstalllocalregionsintheimage.RobertCollinsCSE486,PennStateObserveandGeneralizeKeyidea:Crosscorrelationwithafiltercanbeviewedascomparingalittle“
3、picture”ofwhatyouwanttofindagainstalllocalregionsintheimage.Minimumresponse:lookslikeverticaledge;lighteronrightverticaledge;lighteronleftMaximumresponse:verticaledge;lighteronrightRobertCollinsCSE486,PennStateObserveandGeneralizeKeyidea:Crosscorrelationwithafiltercanbeviewedasc
4、omparingalittle“picture”ofwhatyouwanttofindagainstalllocalregionsintheimage.Forthisreason,itissometimescalled“matchedfiltering”Infact,youcanprovethatthebestlinearoperatorforfindinganimagepatchisessentiallythepatchitself(usingvariationalcalculus,outsidescopeofourcourse).RobertCol
5、linsCSE486,PennStateTemplateMatchingWhatifwecutlittlepicturesoutfromanimage,thentriedconvolvethemwiththesameorotherimages?RobertCollinsCSE486,PennStateTemplateMatching*RobertCollinsCSE486,PennStateTemplateMatching*RobertCollinsCSE486,PennStateConfessionI’vecheatedalittlebit.Isub
6、tractedthemeangreyvaluefromboththeimageandthetemplatebeforedoingcrosscorrelation.Why?(wewilldiscusslater,butthinkaboutitfirst)RobertCollinsCSE486,PennStateCorrespondenceProblemVisiontaskssuchasstereoandmotionestimationrequirefindingcorrespondingfeaturesacrosstwoormoreviews.Rober
7、tCollinsCSE486,PennStateTheCorrespondenceProblem•Basicassumptions:–Mostscenepointsarevisibleinbothimages–Correspondingimageregionsaresimilar•Theseassumptionsholdif:–ThedistanceofpointsfromthecamerasismuchlargerthanthedistancebetweencamerasCamps,PSURobertCollinsCSE486,PennStateTh
8、eCorrespondenceProblem•Isa“search”problem:–Give
