Table Of Content

Mathematics and Visualization SeriesEditors GeraldFarin Hans-ChristianHege DavidHoffman ChristopherR.Johnson KonradPolthier MartinRumpf Georges-Pierre Bonneau Thomas Ertl Gregory M. Nielson Editors Scientific Visualization: The Visual Extraction of Knowledge from Data With 228 Figures ABC Georges-PierreBonneau GregoryM.Nielson UniversiteGrenobleI DepartmentofComputerScienceandEngineering Lab.LMC-IMAG IraA.FultonSchoolofEngineering BP53,38041GrenobleCX9 ArizonaStateUniversity France Tempe,AZ85287-8809 E-mail:[email protected] USA E-mail:[email protected] ThomasErtl UniversityofStuttgart VisualizationandInteractiveSystems Institute(VIS) Universitätßtraße38 70569Stuttgart Germany E-mail:[email protected] LibraryofCongressControlNumber:2005932239 MathematicsSubjectClassification:68-XX,68Uxx,68U05,65-XX,65Dxx,65D18 ISBN-10 3-540-26066-8SpringerBerlinHeidelbergNewYork ISBN-13 978-3-540-26066-0SpringerBerlinHeidelbergNewYork Thisworkissubjecttocopyright.Allrightsarereserved,whetherthewholeorpartofthematerialis concerned,specificallytherightsoftranslation,reprinting,reuseofillustrations,recitation,broadcasting, reproductiononmicrofilmorinanyotherway,andstorageindatabanks.Duplicationofthispublication orpartsthereofispermittedonlyundertheprovisionsoftheGermanCopyrightLawofSeptember9, 1965,initscurrentversion,andpermissionforusemustalwaysbeobtainedfromSpringer.Violationsare liableforprosecutionundertheGermanCopyrightLaw. SpringerisapartofSpringerScience+BusinessMedia springeronline.com (cid:1)c Springer-VerlagBerlinHeidelberg2006 PrintedinTheNetherlands Theuseofgeneraldescriptivenames,registerednames,trademarks,etc.inthispublicationdoesnotimply, evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfromtherelevantprotectivelaws andregulationsandthereforefreeforgeneraluse. Typesetting:bytheauthorsandTechBooksusingaSpringerLATEXmacropackage Coverdesign:design&productionGmbH,Heidelberg Printedonacid-freepaper SPIN:11430032 46/TechBooks 543210 Preface ScientificVisualizationisconcernedwithtechniquesthatallowscientistsandengi- neers to extract knowledge from the results of simulations and computations. Ad- vancesinscientificcomputationareallowingmathematicalmodelsandsimulations tobecomeincreasinglycomplexanddetailed.Thisresultsinacloserapproximation torealitythusenhancingthepossibilityofacquiringnewknowledgeandunderstand- ing.Tremendouslylargecollectionsofnumericalvalues,whichcontainagreatdeal of information, are being produced and collected. The problem is to convey all of thisinformationtothescientistsothateffectiveusecanbemadeofthehumancre- ativeandanalyticcapabilities.Thisrequiresamethodofcommunicationwithahigh bandwidthandaneffectiveinterface.Computergeneratedimagesandhumanvision mediated by the principles of perceptual psychology are the means used in scientific visualization to achieve this communication. The foundation material for the techniquesofScientificVisualizationarederivedfrommanyareasincluding,forex- ample, computer graphics, image processing, computer vision, perceptual psychology, applied mathematics, computer aided design, signal processing and numerical analysis. This book is based on selected lectures given by leading experts in Scientific VisualizationduringaworkshopheldatSchlossDagstuhl,Germany.Topicsinclude user issues in visualization, large data visualization, unstructured mesh processing forvisualization,volumetricvisualization,flowvisualization,medicalvisualization andvisualizationsystems.ThemethodsofvisualizingdatadevelopedbyScientific Visualizationresearcherspresentedinthisbookarehavingbroadimpactontheway other scientists, engineers and practitioners are processing and understanding their datafromsensors,simulationsandmathematicsmodels. Wewouldliketoexpressourwarmestthankstotheauthorsandrefereesfortheir hardwork.WewouldalsoliketothankFabienVivodtzevforhishelpinadminister- ingthereviewingandeditingprocess. Grenoble, Georges-PierreBonneau January2005 ThomasErtl GregoryM.Nielson Contents PartI MeshesforVisualization AdaptiveContouringwithQuadraticTetrahedra BenjaminF.Gregorski,DavidF.Wiley,HenryR.Childs,BerndHamann, KennethI.Joy .................................................... 3 OntheConvexificationofUnstructuredGrids fromaScientificVisualizationPerspective JoaõL.D.Comba,JosephS.B.Mitchell,ClaúdioT.Silva ................. 17 BrainMappingUsingTopologyGraphsObtained bySurfaceSegmentation FabienVivodtzev,LarsLinsen, BerndHamann,KennethI.Joy,BrunoA.Olshausen...................... 35 ComputingandDisplayingIntermolecularNegativeVolumeforDocking ChangHaLee,AmitabhVarshney .................................... 49 OptimizedBoundingPolyhedra forGPU-BasedDistanceTransform RonaldPeikert,ChristianSigg ....................................... 65 Generating,Representing andQueryingLevel-Of-DetailTetrahedralMeshes LeilaDeFloriani,EmanueleDanovaro................................ 79 Split’NFit:AdaptiveFitting ofScatteredPointCloudData GregoryM.Nielson,HansHagen,KunLee,AdamHuang ................. 97 VIII Contents PartII VolumeVisualizationandMedicalVisualization RayCastingwithProgrammableGraphicsHardware ManfredWeiler,MartinKraus,StefanGuthe,ThomasErtl,WolfgangStraßer..115 VolumeExplorationMadeEasyUsingFeatureMaps KlausMueller,SarangLakare,ArieKaufman...........................131 FantasticVoyageoftheVirtualColon ArieKaufman,SarangLakare .......................................149 VolumeDenoisingforVisualizingRefraction DavidRodgman,MinChen .........................................163 EmphasizingIsosurfaceEmbeddings inDirectVolumeRendering ShigeoTakahashi,YurikoTakeshima,IsseiFujishiro,GregoryM.Nielson ....185 DiagnosticRelevantVisualization ofVascularStructures ArminKanitsar,DominikFleischmann,RainerWegenkittl,MeisterEduard Gro¨ller .........................................................207 PartIII VectorFieldVisualization CliffordConvolutionandPatternMatching onIrregularGrids JuliaEbling,GerikScheuermann.....................................231 FastandRobustExtraction ofSeparationLineFeatures XavierTricoche,ChristophGarth,GerikScheuermann ...................249 FastVortexAxisCalculationUsingVortexFeatures andIdentificationAlgorithms MarkusRu¨tten,Hans-GeorgPagendarm ...............................265 TopologicalFeaturesinVectorFields ThomasWischgoll,JoergMeyer......................................287 PartIV VisualizationSystems GeneralizingFocus+ContextVisualization HelwigHauser ...................................................305 Contents IX Rule-basedMorphingTechniques forInteractiveClothingCatalogs AchimEbert,IngoGinkel,HansHagen ................................329 APracticalSystemforConstrainedInteractiveWalkthroughs ofArbitrarilyComplexScenes LiningYang,RogerCrawfis .........................................345 ComponentBasedVisualisation ofDIETApplications RolfHendrikvanLengen,PaulMarrow,ThiesBa¨hr,HansHagen,Erwin Bonsma,CefnHoile ...............................................367 FacilitatingtheVisualAnalysis ofLarge-ScaleUnsteadyComputationalFluidDynamicsSimulations KellyGaither,DavidS.Ebert........................................385 EvolvingDataflowVisualizationEnvironments toGridComputing KenBrodlie,SallyMason,MartinThompson,MarkWalkleyandJasonWood ..395 EarthquakeVisualizationUsingLarge-scaleGroundMotion andStructuralResponseSimulations JoergMeyer,ThomasWischgoll......................................409 AuthorIndex ....................................................433 Part I Meshes for Visualization Adaptive Contouring with Quadratic Tetrahedra BenjaminF.Gregorski1,DavidF.Wiley1,HenryR.Childs2,BerndHamann1,and KennethI.Joy1 1 InstituteForDataAnalysisandVisualization UniversityofCalifornia,Davis bfgregorski,dfwiley,bhamann,[email protected] 2 BDivisionLawrenceLivermoreNationalLaboratory [email protected] Summary. We present an algorithm for adaptively extracting and rendering isosurfaces of scalar-valued volume datasets represented by quadratic tetrahedra. Hierarchical tetrahedral meshes created by longest-edge bisection are used to construct a multiresolution C0-continuousrepresentationusingquadraticbasisfunctions.Anewalgorithmallowsusto contourhigher-ordervolumeelementsefficiently. 1 Introduction Isosurface extraction is a fundamental algorithm for visualizing volume datasets. Most research concerning isosurface extraction has focused on improving the per- formance and quality of the extracted isosurface. Hierarchical data structures, such asthosepresentedin[2,10,22],canquicklydeterminewhichregionsofthedataset containtheisosurface,minimizingthenumberofcellsexamined.Thesealgorithms extract the isosurface from the highest resolution mesh. Adaptive refinement algo- rithms[4,5,7]progressivelyextractisosurfacesfromlowerresolutionvolumes,and controlthequalityoftheisosurfaceusinguserspecifiedparameters. Anisosurfaceistypicallyrepresentedasapiecewiselinearsurface.Fordatasets thatcontainsmooth,steepramps,alargenumberoflinearelementsisoftenneeded to accurately reconstruct the dataset unless extra information is known about the data. Recent research has addressed these problems with linear elements by using higher-ordermethodsthatincorporateadditionalinformationintotheisosurfaceex- tractionalgorithm.In[9],anextendedmarchingcubesalgorithm,basedongradient information, is used to extract contours from distance volumes that contain sharp features.Cellsthatcontainfeaturesarecontouredbyinsertingnewverticesthatmin- imizeanerrorfunction.Higher-orderdistancefieldsarealsodescribedin[12].This approachconstructsadistancefieldrepresentationwhereeachvoxelhasacomplete descriptionofallsurfaceregionsthatcontributetothelocaldistancefield.Usingthis representation,sharpfeaturesanddiscontinuitiesareaccuratelyrepresentedastheir exact locations are recorded. Ju et al. [11] describe a dual contouring scheme for 4 B.F.Gregorskietal. adaptivelyrefinedvolumesrepresentedwithHermitedatathatdoesnothavetotest forsharpfeatures.Theiralgorithmusesanewrepresentationforquadricerrorfunc- tions to quickly and accurately position vertices within cells according to gradient information.Wileyetal.[19,20]usequadraticelementsforhierarchicalapproxima- tionandvisualizationofimageandvolumedata.Theyshowthatquadraticelements, insteadoflinearelements,canbeeffectivelyusedtoapproximatetwoandthreedi- mensionalfunctions. Higher-orderelements,suchasquadratictetrahedraandquadratichexahedra,are used in finite element solutions to reduce the number of elements and improve the qualityofnumerical solutions [18].Since few algorithmsdirectlyvisualize higher- orderelements,theyareusuallytessellatedbyseverallinearelements.Conventional visualization methods, such as contouring, ray casting, and slicing, are applied to theselinearelements.Usinglinearelementsincreasesthenumberofprimitives,i.e. trianglesorvoxels,thatneedtobeprocessed.Methodsforvisualizinghigher-order elementsdirectlyaredesirable. We use a tetrahedral mesh, constructed by longest-edge bisection as presented in[5],tocreateamultiresolutiondatarepresentation.Thelineartetrahedralelements usedinpreviousmethodsarereplacedwithquadratictetrahedra.Theresultingmesh definesaC0-continuous,piecewisequadraticapproximationoftheoriginaldataset. Thisquadraticrepresentationiscomputedinapreprocessingstepbyapproximating thedatavaluesalongeachedgeofatetrahedronwithaquadraticfunctionthatinter- polatestheendpointvalues.Aquadratictetrahedronisconstructedfromthecurves alongitssixedges.Atruntime,thehierarchicalapproximationistraversedtoapprox- imatetheoriginaldatasettowithinauserdefinederrortolerance.Theisosurfaceis extracteddirectlyfromthequadratictetrahedra. The remainder of our paper is structured as follows: Section 2 reviews related work. Section 3describes what quadratic tetrahedra are, and Sect. 4describes how theyareusedtobuildamultiresolutionrepresentationofavolumedataset.Sections5 describeshowaquadratictetiscontoured.OurresultsareshowninSect.6. 2 PreviousWork Tetrahedral meshes constructed by longest-edge bisection have been used in many visualization applications due to their simple, elegant, and crack-preventing adap- tiverefinementproperties.In[5],fine-to-coarseandcoarse-to-finemeshrefinement is used to adaptively extract isosurfaces from volume datasets. Gerstner and Pa- jarola[7]presentanalgorithmforpreservingthetopologyofanextractedisosurface usingacoarse-to-finerefinementschemeassuminglinearinterpolationwithinatetra- hedron.Theiralgorithmcanbeusedtoextracttopology-preservingisosurfacesorto perform controlled topology simplification. In [6], Gerstner shows how to render multipletransparentisosurfacesusingthesetetrahedralmeshes,andin[8],Gerstner andRumpfparallelizetheisosurfaceextractionbyassigningportionsofthebinary tree created by the tetrahedral refinement to different processors. Roxborough and Nielson [16] describe a method for adaptively modeling 3D ultrasound data. They