专业英语 gis 遥感 摄影测量

InteractivelyModelingwithPhotogrammetryWedescribeaninteractivesystemtoreconstruct3Dgeometryandextracttexturesfromasetofphotographstakenwitharbitrarycameraparameters.Thebasicideaistolettheuserdraw2Dgeometryontheimagesandsetconstraintsusingthesedrawings.Becausetheinputcomesdirectlyfromtheuser,hecanmoreeasilyresolvemostoftheambiguitiesanddifficultiestraditionalcomputervisionalgorithmsmustdealwith.Asetofgeometricallinearconstraintsformulatedasaweightedleast-squaresproblemisefficientlysolvedforthecameraparameters,andthenforthe3Dgeometry.Iterationsbetweenthesetwostepsleadtoimprovementsonbothresults.Onceasatisfying3Dmodelisreconstructed,itscolortexturesareextractedbysamplingtheprojectedtexelsinthecorrespondingimages.Allthetexturesassociatedwithapolygonarethenfittedtooneanother,andthecorrespondingcolorsarecombinedaccordingtoasetofcriteriainordertoformauniquetexture.Thesystemproduces3Dmodelsandenvironmentsmoresuitableforrealisticimagesynthesisandcomputeraugmentedreality.Realismincomputergraphicshasgreatlyevolvedoverthepastdecade.Howeververyfewsyntheticimagessimulatingrealenvironmentscanfoolanobserver.Amajordifficultylieswiththe3Dmodels;creatingrealisticmodelsisanexpensiveandtediousprocess.Unfortunatelythegrowingneedforthislevelofaccuracyisessentialforrealisticimagesynthesis,moviespecialeffects,andcomputeraugmentedreality.Oneattractivedirectionistoextractthesemodelsfromrealphotographs.Althoughtwodecadesofcomputervisionresearchhasledtoimportantfundamentalresults,afullyautomatedandreliablereconstructionalgorithmingeneralsituationshasnotyetbeenpresented,atleastfor3Dmodelssatisfyingcomputergraphicsgeneralrequirements.Misinformationincomputervisionalgorithmsresultingfromfalsecorrespondences,missededgedetections,noise,etc.cancreateseveredifficultiesintheextracted3Dmodels.Webaseourpremiseonthefactthattheuserknowswhathewantstomodel,andwithinwhichaccuracy.Hecandecidewhatmustbemodeledbygeometry,andwhatcouldbesimulatedbyasimplergeometrywithatextureappliedonit.Toprovidethisfunctionality,wedevelopedafullyinteractivereconstructionsystem.Gettinganaccurate3Dmodelrequiresthesolutionofseveralproblems,whichareallinterrelated.Wemustfirstcomputecorrectcameraparameters,andthenusethecamerasandconstraintstoreconstructthe3Dgeometry.Afterdiscussingsomerelatedwork,weoutlineourgeometryreconstructionsystem.Asetofcorrespondencesandincidencesresultinsimpleandefficientlinearconstraints.Althoughtheseconstraintsarenotnew,theimprovementsobtainedinaccuracyandspeeddemonstratetheimportanceofconsideringallofthemtogether.Userinterventionateverystepofthisprocess,resultsinmoresatisfyinggeneralreconstructed3Dmodels.Simple3Dgeometrywillbeeffectiveonlywithgoodqualitytextures.WefocusinSection3onamorecomplete,view-independent,treatmentoftextures.Texturesareextractedforeach3Dgeometryfromallimagesitprojectsto.Thebesttexels(2Dtextureelements)arethencombinedintoasingletextureaccordingtovariouscriteriaincludingvisibility,projectedareas,colordifferences,andimagequality.Bysolvingaccuratelyeachproblem,wewillbetterunderstandtherobustness,stability,andprecisionofourtechniques.Itshouldbecomeeasierlaterontoextendourinteractionswithmoreautomaticcomputervisionandimageprocessingtechniquesinordertoalleviatesomeofthemorecumbersomeandtedioustasks,whilekeepinguserinterventionwhererequired.Theresultsofoursystemshouldhelpuscreatemoreprecisetexturedsyntheticmodelsfromreal3Dobjectsinlesstimethancurrent3Dmodelers,andmorerobustlythanfullyautomatedgeometryextractionalgorithms.Twentyyearsofactiveresearchon3Dreconstructionfrom2Dimagesincomputervisionandroboticshaveleftaconsiderablelegacyofimportantresults.Thefirstproblemtoaddressconcernscameracalibration,putingcameraparameters.Thisisadifficultandunstableprocessoftenimprovedbytheuseofspecifictargets.Byputtingincorrespondencepointsorlinesbetweenimages,itbecomespossibletocalibratecameras.Similarlywithknowncameraparameters,onecanreconstructa3Dsceneuptoascalefactor.Intheseclassicalapproaches,segmentationsandcorrespondencesareautomaticallydetermined.OnetypicalexampleoftheresultsobtainedbytheseapproacheswasrecentlypresentedbySatoetal..AfewrecentprojectssuchasREALISE,Fac¸ade,PhotoModelerandAIDAproposetointegratemoreuserinterventionintothereconstructionprocess.Theyarederivedfromprojectivegeometry,andareappliedtothereconstructionofman-madescenesfromasetofphotographsandcorrespondences.REALISEintegratesuserinterventionearlyinthecorrespondenceprocess,lettingtheuserspecifythefirstcorrespondences,andthenreturningtoamoreclassicalapproachtoidentifyautomaticallymostoftheothercorrespondences.Themorestableinitialsolutiongreatlyhelpstoreducetheerrorsofsubsequentiterations.Neverthelessthesameerrorsoffullyautomaticsystemscanstilloccur,andtheusermustthendetectandcorrecttheoriginoftheerrors,whichisnotasimpletaskasthenumberofautomaticcorrespondencesincreases.Fac¸adedevelopsaseriesofparameterizedblockprimitives.Eachblockencodesefficientlyandhierarchicallyseveralconstraintsfrequentlypresentinarchitecturaldesign.Theusermustfirstplacetheblockswitha3Dmodeler,andthensetcorrespondencesbetweentheimagesandtheseblocks.Non-linearoptimizationofanobjectivefunctionisthenusedtosolveforalltheseconstraints.Thesystemhasproventobequiteefficientandprovidesprecise3Dmodelswithlittleeffort.Howeveritrequirestheusertobuildwiththeblocksthemodelhewantstoreconstruct.Webelievethismightbemoredifficultwhengeneral3Dmodelscannotbeaseasilycreatedwiththeseblocks.PhotoModelerisacommercialsoftwareforperformingphotogrammetricmeasurementsonmodelsbuiltfromphotographs.Oncethecameraiscalibrated,theuserhastoindicatefeaturesandcorrespondencesontheimages,andthesystemcomputesthe3Dscene.Themodelsobtainedappearquitegood,althoughitseemstobealengthyprocess(theyreportedaweekforamodelof2003Dpoints)whichusesimagesofveryhighresolution(around15MBeach).Wealsonoticedmanylongthintrianglesandgapsinsomeoftheirmodels.Thesystemcanapplytexturescomingfromthephotographsbutdoesnotseemtoperformanyparticulartreatmentsincetheshadows,highlights,etc.arestillpresent.Nodetailsareprovidedonthealgorithmsused.TheAIDAsystemisafullyautomaticreconstructionsystemthatcombinessurfacereconstructiontechniqueswithobjectrecognitionforthegenerationof3Dmodelsforcomputergraphicsapplications.Thesystempossessesaknowledgedatabaseofconstraints,andselectstheconstraintstoapplytothesurfaceunderreconstructionafterperformingasceneinterpretationphase.Webelieveitmightbesafer,lesscumbersome,andmoregeneraltolettheuserchoosewhichconstraintshewantstoapplytoits3Dprimitivesratherthanlettingthesystempicksomeconstraintsfromaknowledgedatabasecreatedspecificallyforthetypeofscenetoreconstruct.Forthesereasons,weintroduceasystemessentiallybasedonuserinteraction.Theuserisresponsiblefor(almost)everything,butalsohasthecontrolon(almost)everything.Thisshouldprovideacomprehensivetooltoimproveonthemodelingfromreal3Dobjectsandonthecomputergraphicsqualityofthese3Dmodels,whileofferingtheopportunitytofocusonthedetailsimportanttothedesigner.SystemOverview.Wehavedevelopedaninteractivereconstructionsystemfromimages.Theimagesdefinethecanvasonwhichallinteractionisbased.Theycancomefromanytypeofcameras(evenavirtualsyntheticcamera)withanysettingsandposition.Theuserdrawspoints,lines,andpolygonsontheimageswhichformourbasic2Dprimitives.Theuserinteractivelyspecifiescorrespondencesbetweenthe2Dprimitivesondifferentimages.Hecanalsoassignotherconstraintsbetweenreconstructed3Dprimitivessimplybyclickingononeoftheirrespective2Dprimitives.Theseadditionalconstraintsincludeparallelism,perpendicularity,planarity,andco-planarity.Atanytime,theusercanaskthesystemtoreconstructallcomputablecamerasand3Dprimitives.Thereconstructed3Dprimitivescanbereprojectedontheimagestoestimatethequalityofeachrecoveredcameraandthe3Dprimitives.Theuserthenhasthechoicetoiterateafewtimestoimproveonthemathematicalsolution,ortoaddnew2Dprimitives,correspondences,andconstraintstorefinethe3Dmodels.Thisprocess,illustratedinFig.1,demonstratestheflexibilityandpowerofourtechnique.The3Dmodelisreconstructedincrementally,refinedwhereandwhennecessary.Eacherrorfromtheusercanalsobeimmediatelydetectedusingreprojection.ContrarilytoDebevecetal.,theuserdoesnotcreateasyntheticmodelofthegeometryhewantstorecover,althoughthereconstructed3Dmodelcanaseasilybeusedtoestablishnewconstraintsbetween2Dandreconstructed3Dprimitives.Eachimagethuscontainsasetof2Dprimitivesdrawnonit,andacameracomputedwhenthesetofresolvedconstraintsissufficient.Tobootstrapthereconstructionprocess,theuserassignsasufficientnumberof3Dcoordinatesto3Dprimitivesviaoneoftheircorresponding2Dprimitives.Forinstance,six3Dpointsinoneimageallowthecomputationofthecorrespondingcamera.Oncetwocamerasarecomputed,all3Dgeometrythatcanbecomputedbyresolvingtheconstraintsisreconstructed.Withtheassignedandthenewlycomputed3Dvalues,theconstraintsareresolvedagaintoimprovethereconstructedcameras.Thisprocessiteratesuntilnomoreconstraintscanberesolved,andthe3Dgeometryandcamerasarecomputedtoasatisfactoryprecision.Typically,aconvergenceiterationsolvingtheequationsystemsforcomputingallthecamerasand3Dpositionstakesbetween0.05and2seconds,1dependingonthecomplexityofthescene(50to2003Dpoints)andtheconstraintsused.Allourconstraintsareexpressedaslinearequations,typicallyforminganoverdeterminedsetofequations.Aleast-squaressolutiontothissystemiscomputedbysingularvaluedecomposition.Weusethissolutionfortheunknowncameraparameters,andtheunknown3Dcoordinatesofpointsandlines.Asanexactcorrespondenceishardlyachievablebydrawing2Dpointsontheimageplane,wecomputethebestcameraparametersintheleast-squaressense.Hartleydemonstratesimpleconditionsunderwhichlinearsystemsofequationsusedtodeterminethecameraparametersareaspreciseastheirnon-linearcounterparts.Moreoverthistechniqueissimpletoimplement,efficient,general,alwaysprovidesasolution,andweobservedthatitismorerobustthanthenon-linearsystems.Additional3DConstraints.Mostman-madescenesexhibitsomeformofplanarity,parallelism,perpendicularity,symmetry,etc.Usingcorrespondencesonly,reconstructedgeometryoftendoesnotrespecttheseproperties,whichcanleadtoobjectionableartifactsinthereconstructed3Dmodels.Itisthereforeveryimportanttointegratethistypeofconstraintinareconstructionsystem.Theyareunfortunatelydifficulttodetectautomatically,asperspectiveprojectiondoesnotpreservethemintheimage.Theusercanhoweververyeasilyindicateeachsuchconstraintdirectlyontotheimages.Theyareintegratedintoourconvergenceprocessbyaddingequationstothesystemoflinearequationsusedtocompute3Dcoordinates.Althoughtheyarenotstrictlyenforcedbecausetheyaresimplypartofaleast-squaressolution,theyoftenresultinmoresatisfying3Dmodelsespeciallywithrespecttotheneedsofcomputergraphicsmodels.Coplanarity:Aplanarpolygonwithmorethanthreeverticesshouldhaveallitsverticesonthesameplane.Foreachpolygonwith3Dvertices,weaddaplanarityconstraintoftheformthatwillbeusedduringthecomputationofeach.Polygons,points,andlinescanalsobeconstrainedtolieonthesamesupportingplane.Tocomputethisplane,theusercanspecifyanormaldirection.Wecomputethebestvalueforbyusingtheknown3Dpoints.Ifthereisnoinformationabouttheplaneorientation,wecomputethebestplaneintheleast-squaressense,thatpassesthroughatleastthreeknown3Dpointsofthecoplanarprimitives,andapplythesameconstraint.Parallelism:Similarly,severalpolygonsandlinescanbeparalleltoeachother,providingadditionalconstraints.Foreachpolygon,wegetitsorientationfromitsplaneequation,ifavailable.Theseorientationsallowustocalculateanaverageorientationthatwillbeattributedtoalltheparallelpolygons,eventhoseforwhichnoorientationcouldbefirstcalculated.Aplanarityconstraintisaddedtothecomputationofthepolygons3Dpoints.Forparallellines,wecomputetheiraveragedirection.Perpendicularity:Ifthenormalstoperpendicularpolygonsareknown,wecanaddotherconstraintsforthecomputationof.Twoperpendicularpolygonshaveperpendicularnormals,thusforeverypolygonorthogonaltoasetofparallelpolygons,wehave.Manyotherconstraintsshouldbeexploited.Symmetrycouldconstraincharacteristicssuchaslengthsorangles.Similaritybetweenmodelscouldspecifytwoidenticalelementsatdifferentpositions.Incidenceofpointsandlinescanbeextendedtodifferentprimitives.Theseareonlyafewoftheconstraintsweobservein3Dscenes.Eachbasicconstraintdescribedabovecanbeusedasabuildingblockformoreelaborateprimitives.Acubeforinstancebecomesasetofplanarfaces,withperpendicularityandparallelismbetweenitsfacesandsegments,andconstrainedlengthbetweenits3Dvertices.Ratherthanlettingtheuserspecifyalltheseconstraints,anewprimitiveforwhichallofthesearealreadyhandledrepresentsamuchmoreefficienttoolfortheuser.Thesenewprimitivescanbedescribedinalibraryofprimitivesorganizedhierarchically.Debevecetal.showshowthisrepresentationcanalsoreducesignificantlythenumberofconstraintstoresolve.Wecanalsoweightthecontributionsoftheconstraintsdependingontheirimportanceinthecurrentreconstruction.Thedefaultweightsassignedtoeachtypeofconstraintcanbeeditedbytheuser.Theresolutionofourequationsystemsissimplyextendedtoaweightedleast-squares.ResultsofGeometryReconstructionToevaluatetheprecisionandtheconvergenceofouriterativeprocess,weconstructedasimplesyntheticscenemadeofsevenboxes.FiveimagesofresolutionwhererenderedfromcamerapositionsindicatedbythegreyconesinFig.3(left).2Dpolygonsweremanuallydrawnandputincorrespondenceswithin60minutesona195MHzR10000SGIImpact.The3Dcoordinatesofsixpointsofthecentralcubeonthefloorwereenteredtobootstrapthesystem.ThethreecurvesinFig.3(right)representthedistanceinworldcoordinatesbetweenthereal3Dpositionofthreepointsinthescene((-2,3,0),(0,2,-2),(1,2,-2))andtheirreconstructedcorrespondents.200iterationswithoutanyconstraintsotherthanthepointcorrespondencestookabout5minutes.Wethenappliedsuccessivelytheconstraintsofplanarity,coplanarity,andparallelismbetweenallthe3Dpolygons.Calculatingalltheseconstraintstypicallyaddsafewtenthsofasecondperiterationdependingonthecomplexityofthe3Dscene.Thethreecurvesreachaplateauafteracertainnumberofiterations.Thisdoesnotmeanthatthe3Dmodelisthenperfectlyreconstructed,butratherthatthesolutionisstableandshouldnotchangesignificantlywithmoreiterations.Whenweintroducetheplanarityandthenthecoplanarityconstraintsforindividualpolygons,thepointsmoveslightly.Inthisscenewhereparallelismispreponderant,theadditionofthislastconstraintimprovessignificantlythereconstructionforallthreepoints,whichisshownbythedropofallthreecurvesafteriteration300.Theintroductionofanewconstraintcansometimesperturbthewholesystem,affectingmoretheless-constrainedelementsasdemonstratedbythesuddenspikeincurve2.Inmostobservedcases,thesystemquicklyreturnstoanimprovedandmorestablestate.InFig.3(center),wereprojectinwireframemodethereconstructedmodelusingthecomputedcamerafromoneoftheoriginalimages.Distancesbetweenthe2Ddrawnpointsandthereprojectedreconstructedpointsallliewithinlessthanonepixelfromeachother.When3Dconstraintsareusedtoimprovethemodel,thisdistancecanreachuptotwopixels.The3Dscenethencorrespondsmoretorealitybutdoesnotfitexactlythedrawnprimitiveswhenreprojectedwiththecomputedprojectionmatrix.Theconstraintsthuscompensatefortheinaccuracyintroducedbytheuserinteractionorbytheprimitivesfarfromtheenteredcoordinates.Becausetheuserdraws2Dprimitivesattheresolutionoftheimage,gettingamaximumoftwopixelsisconsideredsatisfactory.Sub-pixelsaccuracyisobtainediftheseprimitivesaredrawnatsub-pixelprecision,butthislengthentheuserinteractiontime.ExtractingTextureTextureshavebeenintroducedincomputergraphicstoincreasetherealismofsyntheticsurfaces.Theyencodeviaasurfaceparameterizationthecolorforeachpointonthesurface.Whilethecontributionoftexturestorealismisobvious,itisnotalwayseasytoextractatexturefromrealimages.Onemustcorrectforperspectiveforeshortening,surfacecurvature,hiddenportionsofthetexture,reflections,shading,etc.Alltheselimitationshaverestrictedthetypeofextractedrealtextures.Howeverourreconstructedgeometryandcamerasprovideagreatcontextwithinwhichwecanextractthesetextures.Mostcurrentapproachesarebasedonview-dependenttextures.Havaldaretal.usetheprojectionofthe3Dprimitiveinalltheimagestodeterminethebestsourceimageforthetexture.Thenweapplytothetexturethe2Dtransformationfromtheprojectedpolygoninthisbestimage,totheprojectedpolygonintheimagefromanewviewpoint.Unfortunately,this2Ddeformationofthetextureisinvalidforaperspectiveprojection,andpronetovisibilityerrors.Debevecetal.reprojectseachextractedtextureforagivenprimitiveasaweightedfunctionbasedontheviewingangleofthenewcameraposition.Thetechniqueprovidesbetterresultswithview-dependentinformation.However,neglectingthedistancefactorintheweightscanintroduceimportanterrors,andaliasingcanappearfromtheuseofocclusionmaps.Moreoverallthetexturesmustbekeptinmemoryaspotentiallyallofthemmightbereprojectedforanynewviewpoint.NiemandBroszioidentifiesthebestimageforanentirepolygon(accordingtoangleanddistancecriteria),andsamplesthetexturefromthisimage.Becauseadjacentpolygonscanhavedifferentbestimages,theythenproceedtosmoothouttheadjacenttexels,possiblyalteringthetextures.Inoursystem,atextureisextracteduponuserrequestforagivenprimitiveprojectinginanumberofimages.Thetextureistheresultofrecombiningtheestimatedbestcolorsforeachpointofthesurfaceprojectedineachimage.Eventhoughextractingasingletextureispronetoerrorsaswillbediscussedlater,itismoresuitableforgeneralimagesynthesisapplicationssuchasapplyingittodifferentprimitives,filtering,anduseofgraphicshardware.Foragiven3Dpoint,itsprojectioninoneimagewillmostlikelybeavisiblepointbecausetheuserdrewitssupporting3Dprimitiveasacorresponding2Dprimitiveontheimage.Howeversomeportionofthe3Dprimitivemightbeblockedbyanother3Dprimitiveclosertotheimageplane,thusleadingtoanincoherentcolor.Asimpletestdeterminesthezonewithanocclusionriskbyintersectingthe2Dprimitivewithall2Dprimitivesonthisimage.Ifthereisintersection,wemustdeterminethe3Dintersectionbetweenthecorresponding2Dpointontheimage(twoplanes)andthepotentiallyoccluding3Dpolygon(athirdplane).Ifthereisintersectionandthedepthissmallerthantheoneofthe3Dpoint,wesimplymarkthisoccludedcolorsampleasinvalid.Weextractacolorforeachtexelineachimage.Thefinalcolorforthistexelmustbecomputedfromthesecolors.Thesizeinpixelsofthetexelprojectedintheimageisagoodindicationofthequalityofthecolorextractedforthistexel.Thelargertheprojectedareaofatexel,themoreprecisethetextureshouldbe.Therefore,forallthevalidcolorsofagiventexel,weweightitscolorcontributionasarelativefunctionoftheprojectedareasofthetexelinallselectedimages.Ofeketal.storeseachpixelineachimageintoamipmappyramidalstructureforthetexture.Colorinformationispropagatedupanddownthepyramid,withsomeindicationofcertaintyaccordingtocolorvariations.Thestructurefitseachtexeltotheimagepixelresolution,thusadaptingitsprocessingaccordingly.Howeverunlessveryhighresolutiontexturesarerequired,webelievetheextracostofpropagatingtheinformationinthepyramidandtheinevitablelossofinformationduetothefilteringbetweenlevelsmightnotbeworththesavings.Oursolutionissimple,butmightrequiresamplingmanytexelsprojectingwithinasmallfractionofapixelarea.Howeverallinformationiskeptattheuser-specifiedtexelresolution,andassuch,wegetmuchflexibilityinwaysofinterpretingandfilteringtheinformation.Itisalsofairlysimpletointegratevariousnewcriteriatoimproveontheprocessofcombiningtheextractedtexels.Unfortunatelywemustbeawarethatseveralsituationsmightinvalidateanysuchtextureextractionalgorithm.Anyview-dependentfeaturethatchangestheaspect(color)ofa3Dpointasthecameramovesmightbeasourceoferrors.Theseincludespecularreflections(highlights),mirrors,transparencies,refractions,ignoredsurfacedeformations(sharpgroovesandpeaks),participatingmedia,etc.Withoutuserintervention,acombinationoftheseartifactscanhardlybehandledautomatically.Whenonecoloratonetexelisverydifferentthantheothersfordifferentimages,wesimplyrejectitscontribution,assumingitwascausedbyview-dependentfeaturesornoiseintheimage.Whenallthecolorsareverydifferentfromeachother,wesimplymarkthistexelasinvalid.Wewilldiscussintheconclusionhowthesedifferencescouldbeusedtoextractsuchview-dependentinformation.Thecolorofapixelatsilhouettesandedgesofpolygonsincludesnotonlythetexelcolor,butalsobackgroundandothergeometrycolors.Cameraregistrationerrorsalsointroduceslightmisalignmentsbetweenthereconstructed3Dprimitiveandeach2Dprimitiveitshouldprojectto.Weagainsimplymarksuchatexelasinvalid.Wethereforeendoutwithanextractedtexturewithsomeundefinedtexelcolors.Fortunately,thesetypicallyrepresentasmallportionoftheentiretexture.Wecurrentlyfillinthesetexelsbyapplyingasimplefilter,althoughsomefillingalgorithmshaveproventobequiteefficient.Theyshouldbeevenmoreeffectiveforgapsasnarrowasthoseobservedsofarinourtests.交互式建模与摄影我们描述一个互动系统，以重建三维几何，并从中提取了与任意摄像机拍摄的照片设置纹理参数。其基本思想是让用户在图像上绘制二维几何和设置限制使用这些图纸。由于输入直接来自用户，他可以更容易地解决困难的含糊和最传统的计算机视觉算法必须处理的问题。作为一个加权最小二乘问题制定一套几何线性约束有效地解决了相机的参数，然后三维几何图形。这两个步骤迭代导致两种结果的改善上。一旦满足三维模型重建，它的颜色纹理提取样品在相应的图像投影纹理元素。所有与多边形关联的纹理，然后再装一个，及相应的颜色组合根据一套标准，以形成独特的质感。该系统产生的3D模型和环境，更逼真的图像合成和增强现实合适的电脑。在计算机图形学中的现实主义已经发生巨大变化，在过去的10年。但很少能模拟真实环境愚弄观察员合成图像。一个主要的困难在于三维模型，创造现实的模式是一个昂贵和繁琐的过程。不幸的是，为达到这一精度水平不断增长的需求是现实的图像合成的必需，电影特效，计算机增强现实。一个有吸引力的方向是从实际中提取的照片，这些模式。虽然两名计算机视觉研究数十年，导致重要的基本成果，在一般情况下完全自动化和可靠的重建算法尚未提交，至少在计算机图形三维模型满足一般要求。在计算机视觉算法，从虚假的误导造成的书信，错过了边缘检测，噪声等，可以建立三维模型中提取的严重困难。我们立足于一个事实，即用户知道他要什么型号，我们在其中的准确性的前提。他可以决定什么必须由几何模型，以及可以通过一个与它应用了一个简单的几何纹理模拟。为了实现这一功能，我们开发了一个完全互动的重建系统。得到一个准确的三维模型需要几个问题，这些问题都是相互关联的解决方案。我们首先必须计算正确的摄像机参数，然后使用相机和约束的三维几何重建。在讨论了一些相关的工作，我们阐明我们的几何重建系统。一种简单的书信和发病率和有效率的线性限制结果集。虽然这些限制是不是新的，改进的精度和速度获得展示了它们放在一起考虑的重要性。用户在这个过程的每一步，在一般的结果更令人满意的干预重建的三维模型。简单的三维几何结构将会只有具备良好素质的纹理效果。我们集中更完整，观点独立，纹理处理。每个纹理提取所有图像三维的几何项目。最好的纹理元素（2D纹理元素），然后合并成一个单一的纹理根据不同的标准包括能见度，投影面积，颜色的差异，以及图像质量。通过准确地解决每一个问题，我们将更好地了解鲁棒性，稳定性，和我们的技术精度。它应该成为日后在社会上更容易更自动延长计算机视觉和图像处理技术的相互作用，以减轻较繁琐，繁琐的一些任务，同时保持在需要用户干预。我们系统的结果应有助于我们建立在更短的时间比目前的立体模型更精确的实时纹理合成三维物体模型，以及更强劲的几何比全自动提取算法。20年来积极研究从二维三维重建在计算机视觉和机器人形象留下了一个重要的结果。第一个问题，解决问题相机标定，即计算摄像机参数。这是一个困难和不稳定的过程通常由使用改进的具体目标。通过在图像间对应点或线推杆，就有可能以校准相机。同样已知摄像机参数，可以重建一个三维场景最多，其规模因素。在这些经典的方法，分割及书信自动确定。通过这些方法之一所取得的成果典型的例子是最近提出的佐藤等人。他们是从射影几何派生，并应用于人造从照片和书信集场景重建。结合用户干预早在对应过程中，让用户指定的第一书信来往，然后回到一个更经典的方式来确定自动成为其他通讯最。较稳定的初步方案大大有助于减少以后的迭代中的错误。不过全自动系统仍然可以出现同样的错误，并且用户必须再检测和纠正错误，这不是作为简单的数量的增加自动对应任务的起源。外交事务委员会¸开发了一系列的参数块图元。每个块编码效率和层次结构在建筑设计中经常出席一些制约因素。用户必须先在三维建模与块之间，以及与这些图像块然后设置对应。非线性优化的目标函数，然后用于解决所有这些限制。该系统已被证明是相当有效的，并提供精确的三维模型与不费吹灰之力。但它要求用户与块建设模式，他希望重建。我们认为这可能是比较困难时，一般的三维模型可以很容易被这些块创建。是从照片上执行建立摄影测量模型的商业软件。一旦相机校准，用户在图像上显示的功能及通信，计算和系统的三维场景。这些模型得出似乎相当不错，虽然这似乎是一个漫长的过程（他们报告了1200点的三维模型1周），它使用了非常高清晰度图像（约15MB的每个）。我们也注意到在一些型号的许多细长的三角形和差距。该系统可以应用纹理从照片来，但似乎没有执行，因为任何特定的阴影处理，重点等依然存在。没有任何细节上的算法来提供。阿伊达系统，是一个完全自动重建系统，它结合了对象的三维计算机图形应用模型生成识别表面重建技术。该系统具有知识数据库的限制，并选择适用的限制下到地面后重建执行现场解释阶段。我们认为这可能是更安全，减少麻烦，并让更多的普通用户选择的限制，他要申请，而不是让系统挑选创造了具体的场景类型重建一个知识数据库中的一些限制，它的三维图元。基于这些原因，我们基本上介绍用户交互为基础的系统。用户是负责（几乎）一切，但也有对（几乎）所有的控制权。这应提供全面的工具，从真正改善3D物体建模和计算机图形处理这些三维模型的质量，同时提供机会，把重点放在重要的细节设计。系统概述。我们已经发展到一个互动的图像重建系统。这些图像定义上所有的互动为基础的画布。他们可以来自任何类型的相机（甚至是虚拟合成相机）与任何设置和位置。用户绘制点，线，和我们的形象，构成基本的2D图元多边形。用户以交互方式指定不同的图像之间的二维图元对应。他也可以通过简单地分配各自的二维图元一点击重建三维图元之间的其他限制。这些额外的限制，包括平行度，垂直度，平面和共面。在任何时候，用户可以要求系统重建所有可计算的相机和三维图元。重建后的三维图元，可投射的图像来估计每回收的三维图元摄像头和质量。然后，用户的选择来迭代几次改进的数学解决方案，或增加新的二维图元，书信和约束，以完善的三维模型。这个过程，如图所示。这表明我们的灵活性和技术力量。重建的三维模型，逐步，精在有需要时。从用户的每个错误也可以立即检测到使用再投影。用户不会创建一个几何，他要收回综合模型，虽然重建的三维模型可以很容易被用来作为之间建立二维和三维图元重建新的限制。因此，每一个图像上包含了绘制二维原语集，并计算相机时，解决制约集就足够了。要引导重建过程中，用户分配一个足够数量的三维坐标的三维图元通过其相应的二维元件之一。例如，允许在一个6点的三维图像中相应的相机计算。一旦两个摄像头计算，所有的3D几何可以被解决的制约因素计算重构。随着新的分配和三维计算值，约束决心再次提高重建相机。这个过程循环，直到没有更多的约束可以解决，和相机的三维几何计算，以一个令人满意的精度。通常情况下，收敛迭代求解计算所有的摄影机和3D位置的方程系统需要在0.05和2秒，1对现场（50至200三维分）和复杂程度的限制使用。我们所有的约束条件表示为线