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1、!RFoundationsandTrendsinComputerGraphicsandVisionVol.3,No.3(2007)177–280!c2008T.TuytelaarsandK.MikolajczykDOI:10.1561/0600000017LocalInvariantFeatureDetectors:ASurveyTinneTuytelaars1andKrystianMikolajczyk21DepartmentofElectricalEngineering,KatholiekeUniversiteitLeuven,KasteelparkA
2、renberg10,B-3001Leuven,Belgium,Tinne.Tuytelaars@esat.kuleuven.be2SchoolofElectronicsandPhysicalSciences,UniversityofSurrey,Guildford,Surrey,GU27XH,UK,K.Mikolajczyk@surrey.ac.ukAbstractInthissurvey,wegiveanoverviewofinvariantinterestpointdetectors,howtheyevolvedovertime,howtheywork
3、,andwhattheirrespectivestrengthsandweaknessesare.Webeginwithdefiningthepropertiesoftheideallocalfeaturedetector.Thisisfollowedbyanoverviewoftheliteratureoverthepastfourdecadesorganizedindifferentcategoriesoffeatureextractionmethods.Wethenprovideamoredetailedanalysisofaselectionofmet
4、hodswhichhadaparticularlysignificantimpactontheresearchfield.Weconcludewithasummaryandpromisingfutureresearchdirections.1IntroductionInthissection,wediscusstheverynatureoflocal(invariant)fea-tures.Whatdowemeanwiththisterm?Whatistheadvantageofusinglocalfeatures?Whatcanwedowiththem?Wh
5、atwouldtheideallocalfeaturelooklike?Thesearesomeofthequestionsweattempttoanswer.1.1WhatareLocalFeatures?Alocalfeatureisanimagepatternwhichdiffersfromitsimmediateneighborhood.Itisusuallyassociatedwithachangeofanimageprop-ertyorseveralpropertiessimultaneously,althoughitisnotnecessari
6、lylocalizedexactlyonthischange.Theimagepropertiescommonlycon-sideredareintensity,color,andtexture.Figure1.1showssomeexam-plesoflocalfeaturesinacontourimage(left)aswellasinagrayvalueimage(right).Localfeaturescanbepoints,butalsoedgelsorsmallimagepatches.Typically,somemeasurementsare
7、takenfromaregioncenteredonalocalfeatureandconvertedintodescriptors.Thedescrip-torscanthenbeusedforvariousapplications.1781.2WhyLocalFeatures?179Fig.1.1Importanceofcornersandjunctionsinvisualrecognition[20]andanimageexamplewithinterestpointsprovidedbyacornerdetector(cf.Section3.2).
8、1.2WhyLocalFeatures?Asdiscussedsh
