Nonlinear Least Squares Optimisation of Unit Quaternion Func(3)
发布时间:2021-06-06
发布时间:2021-06-06
Pose estimation from an arbitrary number of 2-D to 3-D feature correspondences is often done by minimising a nonlinear criterion function using one of the minimal representations for the orientation. However, there are many advantages in using unit quatern
Figure1.Stereoimagepairshowingthelineseg-mentsextractedfromoneimageandtheedgesofthelocalisedobjectsprojectedontotheotherimageOurgoalistodevelopamethodfortheminimisationof(5)over(t,q)∈R3×S3.Toachievethiswewrite(5)as
13 MN2hk(ti+d,exp(ω) qi)2=1
gi(d,ω)Tgi(d,ω).k=1
2(15)
Usingthesameapproachasinthecaseofpureunitquater-nionfunctions,theGauss-NewtoniterationonR3×S3canbeformulatedasfollows
ti+1
=ti+di,
qi+1=exp(ωi) qi,
(16)
dTi
ωi
T
T=
(JTiJi)
1JTigi
(0,0),whereJiistheJacobianofgiat(0,0).Thisiterationgen-eratesasequencewhichisguaranteedtolieinthesearch
spaceR3×S3.Sincetherearenoconversionsoforien-tationinsomeforeignform,suchasEuler’sangles,toaquaternionform,thenon-uniquenessofthequaternionrep-resentationdoesnotcauseanyproblems.SincethemetricstructureofSO(3)isthesameastheoneofS3,theaboveiterationmaybeviewedasaniterationinR3×SO(3).
4.Experimentalresultsandconclusions
Tovalidatetheproposedmethodexperimentally,weuseditforthecalculationofobjects’posesfromlineseg-mentcorrespondencesinasystemforobjectrecognitionandlocalisation(seeFig.1).TheconvergenceofthemethodisshowninTab.1.Evenwhenthestartingpointwasveryinaccurate,theGauss-Newtonmethodconvergedtothetrueobjectposeprovidedthefeaturecorrespondenceswerecorrect.HencethereisnoneedtousemorerobusttechniquesliketheLevenberg-Marquardtmethodforposeveri cationincalibratedstereoimages.Assumingthatfea-turecorrespondencesarecorrectandthemeasurementnoiseismoderate,thecriterionfunction(15)tendstozerointheneighbourhoodofthesolutionandtheconvergenceofthemethodisnearlyasgoodastheconvergenceoftheNewton-Raphsoniteration.
Table1.Convergenceofthemethod.TheEuclideanandtheangularmetricwereusedtomeasurethechangeinthepositionandorientation,respectively.
Step(trans.)Step(orien.)4.962116e+012.827351e-011.095884e+01
7.604011e-022.851983e-012.920441e-037.462760e-041.835331e-052.017427e-06
1.241607e-07
Furtherexperimentsshouldbecarriedouttotestthemethodforthecasewhenonlyonecameraisavailable.Thepresentedmethodisgeneralandworkswithanykindoffea-tures.Theusageoflineorpointcorrespondencesrequiresonlyarede nitionoffunctionf,whichisde nedforthecaseoflinesegmentsinEq.(3).
ComparingourapproachwiththeoneofPhongetal.[4],whoalsousedquaternionstorepresenttheorientation,ouriterationhastheadvantagethatitsearchesfortheoptimalorientationdirectlyinS3andnotinR4asthemethodofPhongetal.Phongetal.hadtointroduceapenaltytermtoforcetheminimumoftheircriteriontotendtowardsS3.However,thispenaltytermrequiresthesettingofauser-de nedparameterwhichisatbestarbitraryandcancauseproblemswiththeconvergenceoftheiteration.Ourmethoddoesnotsufferfromthisproblem.Moreover,itispossibletodeterminethesearchdirectionusingthetrustregionap-proachofPhongetal.inouriterationandthusmakeitlesssensitivetothequalityofastartingpointandwrongcorre-spondences.Thiswasnotnecessaryforourapplication.Acknowledgment:ThemeasurementsweretakenwhiletheauthorwaswiththeInstituteforReal-TimeComputerSystemsandRobotics,UniversityofKarlsruhe,Germany.
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