特征描述算子评测.doc

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1、FeaturedescriptorcomparisonreportSharingmyresearchworkofbehaviorofseveraltypesoffeaturedescriptors.Thisarticleisanupdateofold"Comparisonoffeaturedescriptors"post.I'veaddedabrandnewORBfeaturedescriptortothetestsuite,alsoSIFTdescriptorincludedaswell.Andanewversiono

2、fLAZYdescriptorpresentinthistesttoo.Forthistestihavewrittenspecialtestframework,whichallowsmetoeasilyaddthenewkindofdescriptorsandtestcasesandgeneratereportdatainCSV-likeformat.ThaniuploaditinGoogledocsandcreatethisawesomecharts.Fivequalityandoneperformancetestwa

3、sdoneforeachkindofdescriptor.oRotationtest- thistestshowshowthefeaturedescriptordependsonfeatureorientation.oScalingtest- thistestshowshowthefeaturedescriptordependsonfeaturesize.oBlurtest- thistestshowshowthefeaturedescriptorisrobustagainstblur.oLightingtest- th

4、istestshowshowthefeaturedescriptorisrobustagainstlighting.oPatterndetectiontest-thistestperformsdetectionofplanar平面object(image)ontherealvideo.Incontrasttothesynthetic综合tests,thistestgivesarealpictureoftheoverallstabilityoftheparticulardescriptor.oPerformancetest

5、isameasurementofdescriptionextractiontime.Allqualitytestsworksinsimilarway.Usingagivensourceimagewegenerateasynthetictestdata:transformedimagescorrespondingfeaturepoints.Thetransformationalgorithmdependsontheparticulartest.Fortherotationtestcase,it'stherotationof

6、thesourceimagearoundit'scenterfor360degrees,forscaling-it'sresizingofimagefrom0.25Xto2xsizeoforiginal.Blurtestusesgaussianblurwithseveralstepsandthelightingtestchangestheoverallpicturebrightness.Thepatterndetectiontestdeservesaspecialattention.Thistestisdoneonver

7、ycomplexandnoisy videosequence.Soit'schallengingtaskforanyfeaturedescriptoralgorithmtodemonstrateagoodresultsinthistest.Themetricforallqualitytestsisthepercentofcorrectmatchesbetweenthesourceimageandthetransformedone.Sinceweuseplanarobject,wecaneasilyselecttheinl

8、iersfromallmatchesusingthehomographyestimation.IuseOpenCV'sfunctioncvFindHomographyforthis.Thismetricgivesverygoodandstableresults.Idonooutlierdetectionofmatch