Vis-A-Ware: Integrating Spatial and Non-Spatial Visualization for Visibility-Aware Urban Planning. Thomas Ortner, Johannes Sorger, Harald Steinlechner, Gerd Hesina, Harald Piringer, Eduard Groller. IEEE TVCG 23(2):1139-1151 2017 Matthew Chun
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Vis-A-Ware:IntegratingSpatialandNon-SpatialVisualizationforVisibility-AwareUrbanPlanning.
ThomasOrtner,JohannesSorger,HaraldSteinlechner,Gerd Hesina,HaraldPiringer,EduardGroller.
IEEETVCG23(2):1139-11512017
MatthewChun
HighLevelOverview
• Urbanplanning• Whatisthevisualimpactofnewbuildingsoncityscape?• Howwillitlookfrommultipledifferentperspectives?• Howcanweeasilycomparedifferentbuildingsbeyondsubjectiveperception?
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HighLevelOverview
• Urbanplanning• Whatisthevisualimpactofnewbuildingsoncityscape?• Howwillitlookfrommultipledifferentperspectives?• Howcanweeasilycomparedifferentbuildingsbeyondsubjectiveperception?
• Vis-A-Ware• Qualitativeandquantitativeevaluation,ranking,andcomparisononthedifferenttypesof“visibility”ofcandidatebuildingsfromvariousviewpoints• Linkstogethera3Dspatialurbanviewwithnon-spatialdataformorecontext
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DomainPractice
• Expertscreatevisibilityandlandmarkocclusionmaps
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DomainPractice
• Photomontagesthatoverlayrealimageswithvirtualcandidatebuildings
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DomainPractice
• 3Drenderingfromafewviewpoints• Hapticmodels
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TaskAnalysis
• Withacombinationofabovetechniques,comparecandidatebuildingswithrespecttovisualimpact(CurrentPractices)• Qualitative->Potentialsubjectivebias• Canonlycompareafewviewpointsatatime
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TaskAnalysis
• Withacombinationofabovetechniques,comparecandidatebuildingswithrespecttovisualimpact(CurrentPractices)• Qualitative->Potentialsubjectivebias• Canonlycompareafewviewpointsatatime
• Canwealsocomparecandidatebuildingsinamoreholisticmanner?(SuggestedNewPractice)• Quantitative->Morespecificityindetails(eg.Howoccluded)• Morecomparisonspossible->Multipleviewpoints
• Isitpossibletocombinethecurrentandnewapproaches?
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RelatedWork
• Occlusionculling
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RelatedWork
• Occlusionculling• GeographicInfoSystem(GIS)
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RelatedWork
• Occlusionculling• GeographicInfoSystem(GIS)• MultipleCriteriaDecisionAnalysis(MCDA)• CoordinatedMultipleViews(CMV)
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DesignGoals
• G1:Computeintuitivemetricsforquantifyingvisualimpactofcandidateswithrespecttospecificviewpoints
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DesignGoals
• G1:Computeintuitivemetricsforquantifyingvisualimpactofcandidateswithrespecttospecificviewpoints• G2:Tightintegrationofspatialviewsandnon-spatialviewstoallowforalinkedanalysisofquantitativeandqualitativedata
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DesignGoals
• G1:Computeintuitivemetricsforquantifyingvisualimpactofcandidateswithrespecttospecificviewpoints• G2:Tightintegrationofspatialviewsandnon-spatialviewstoallowforalinkedanalysisofquantitativeandqualitativedata• G3:Fastidentificationofcandidatesorviewpointsexhibitinghighvisualimpactvalues
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DesignGoals
• G1:Computeintuitivemetricsforquantifyingvisualimpactofcandidateswithrespecttospecificviewpoints• G2:Tightintegrationofspatialviewsandnon-spatialviewstoallowforalinkedanalysisofquantitativeandqualitativedata• G3:Fastidentificationofcandidatesorviewpointsexhibitinghighvisualimpactvalues• G4:Providinganoverviewofthespatialdistributionofviewpointswithhighvisualimpact
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DesignGoals
• G1:Computeintuitivemetricsforquantifyingvisualimpactofcandidateswithrespecttospecificviewpoints• G2:Tightintegrationofspatialviewsandnon-spatialviewstoallowforalinkedanalysisofquantitativeandqualitativedata• G3:Fastidentificationofcandidatesorviewpointsexhibitinghighvisualimpactvalues• G4:Providinganoverviewofthespatialdistributionofviewpointswithhighvisualimpact• G5:Intuitivefiltering,ranking,andcomparisonofcandidatesaswellasviewpoints
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DesignGoals
• G1:Computeintuitivemetricsforquantifyingvisualimpactofcandidateswithrespecttospecificviewpoints• G2:Tightintegrationofspatialviewsandnon-spatialviewstoallowforalinkedanalysisofquantitativeandqualitativedata• G3:Fastidentificationofcandidatesorviewpointsexhibitinghighvisualimpactvalues• G4:Providinganoverviewofthespatialdistributionofviewpointswithhighvisualimpact• G5:Intuitivefiltering,ranking,andcomparisonofcandidatesaswellasviewpoints• G6:Incorporatingexplorationandvisualizationmetaphorsusersarefamiliarwithfromexistingtools
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Video
• https://vimeo.com/183311609
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Vis-A-Ware
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Metrics- Cols
Non-spatial
ViewpointPOV
Spatial
Viewpoints/Candidates- Rows
VisualImpact-Cell
SystemOverview– VisualImpactMetrics(VIM)
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• Codedby“falsecolour”->colour thatstandsoutinascene• Landmarksarered• Skyisblue• Opennessisgreen• Candidatebuildingisorange
SystemOverview– VisualImpactMetrics(VIM)
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• Codedby“falsecolour”->colour thatstandsoutinascene• Landmarksarered• Skyisblue• Opennessisgreen• Candidatebuildingisorange
• Togetanumber,normalizedonaratio• #ofpixelsofVIMofinterest/#ofcandidatepixels
• Bincategories• Low,medium,high,veryhigh
• Howrelevantisparticularviewpoint?• allcandidatepixels/totalnumberofimagepixels
• Bincategories• Small,medium,high
SystemOverview– TransposableRankingView(TRV)
• Mainwaytofilter,rank,comparecandidatesbasedonVIM• DataModel
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TransposableRankingView(TRV)- VisualEncoding
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a) BarchartsshowVIMforeachcandidate(letter)indistribution,saturationshowsimpactclass
ViewpointMajor ModePop-outisforexample
Clickonrowto“expandit”formoredetailedview
TransposableRankingView(TRV)- VisualEncoding
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a) BarchartsshowVIMforeachcandidate(letter)indistribution,saturationshowsimpactclass
b) Stackedbarchartiscompactrep.ofbarcharts
ViewpointMajor ModePop-outisforexample
Clickonrowto“expandit”formoredetailedview
TransposableRankingView(TRV)- VisualEncoding
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a) BarchartsshowVIMforeachcandidate(letter)indistribution,saturationshowsimpactclass
b) Stackedbarchartiscompactrep.ofbarcharts
c) Linkedpeekbrushingshowsdetailondemandandcurrentcandidateacrossotherviewpoints(letter)
ViewpointMajor ModePop-outisforexample
Clickonrowto“expandit”formoredetailedview
TransposableRankingView(TRV)- VisualEncoding
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a) BarchartsshowVIMforeachcandidate(letter)indistribution,saturationshowsimpactclass
b) Stackedbarchartiscompactrep.ofbarcharts
c) Linkedpeekbrushingshowsdetailondemandandcurrentcandidateacrossotherviewpoints(letter)
d) Anyrowthatisrankedbydistributionscoresoverallviewpoints
ViewpointMajor ModePop-outisforexample
Clickonrowto“expandit”formoredetailedview
TransposableRankingView(TRV)- VisualEncoding
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a) BarchartsshowVIMforeachcandidate(letter)indistribution,saturationshowsimpactclass
b) Stackedbarchartiscompactrep.ofbarcharts
c) Linkedpeekbrushingshowsdetailondemandandcurrentcandidateacrossotherviewpoints(letter)
d) Anyrowthatisrankedbydistributionscoresoverallviewpoints
e) Arrowiconloadsintospatialviewoftool(Map)
ViewpointMajor ModePop-outisforexample
Clickonrowto“expandit”formoredetailedview
TransposableRankingView(TRV)- VisualEncoding
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a) BarchartsshowVIMforeachcandidate(letter)indistribution,saturationshowsimpactclass
b) Stackedbarchartiscompactrep.ofbarcharts
c) Linkedpeekbrushingshowsdetailondemandandcurrentcandidateacrossotherviewpoints(letter)
d) Anyrowthatisrankedbydistributionscoresoverallviewpoints
e) Arrowiconloadsintospatialviewoftool(Map)
f) Ahighlevelsummaryofacategoryofviewpoint
ViewpointMajorModePop-outisforexample
Clickonrowto“expandit”formoredetailedview
TransposableRankingView(TRV)– Focus,Filter,TransposeWorkflowExample
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SelecthighimpactVIMportionacrossallviewpoints(CandidateVisibility)ofinterest
TransposableRankingView(TRV)– Focus,Filter,TransposeWorkflowExample
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Focused subsetnowemphasizedwithsplitheightenedbarcharts(left).Remainingdistributionloweredinheightforcontext (right).
TransposableRankingView(TRV)– Focus,Filter,TransposeWorkflowExample
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Canfocusagain.Canexpandarow(vp48)formoredetailedbarchart->exactcandidateVIMvalues
TransposableRankingView(TRV)– Focus,Filter,TransposeWorkflowExample
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Filter/transposeoptiononfocusedset
Usefilteroptionabovetoseefilteredviewpointdistributionsnow.Emphasizefocusedareaforinspection.
TransposableRankingView(TRV)– Focus,Filter,TransposeWorkflowExample
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Transposetoswitchrowordering
Aftertranspose,rowsnowshowpercandidate,viewpointbasedVIMdistributionsonfilteredset
TransposableRankingView(TRV)– Focus,Filter,TransposeWorkflowExample
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Canevenextendfocusedsettootherportionsofdistribution
TransposableRankingView(TRV)– Focus,Filter,TransposeWorkflowExample
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Resultofappendingtofocusedset
TransposableRankingView(TRV)– Focus,Filter,TransposeWorkflowExample
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Canfilteronappendedsubsettoseefocusedareainmoredetail
TransposableRankingView(TRV)– Focus,Filter,TransposeWorkflowExample
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FinaltransposetoseefinalviewpointsbasedonhighimpactVIMcandidates
SystemOverview– 3DSpatialView• Citymodelandassociatedlandmarks,buildings,similartoGIS• Candidatebuildingsdenotedbyrepeating10colours• Viewpointsshownascircularglyphs
• Sizedenoteshowmanycandidatesarecovered• VIMMajoritydenotedbyVIMcolour• Numberdenoteshowmanycandidatesarecovered
• TRVLinkedHighlighting• Onlyviewpointsexpandedrowsshown,otherviewpointsare“context”(greyedout)• Highlightedcandidatebuildingsrenderedopaqueandcoloured ->comparespatialpropertieswithothercandidatesvisually
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SystemOverview- Filmstrip
• BasedonTRVloadedviewpoints/candidates• Showimagesofallcandidatesinoneviewpoint(viewpointmajor)• Showonecandidateinallviewpoints(candidatemajor)
• HeaderinfilmstripboxshowsidentifierofrowfromTRV• NameandvalueofVIMselectedaswell
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TaskAnalysisExample
• Whichcandidatescoveralandmarkandhowstrongistheocclusion?
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UserFeedback
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• Duringdevelopment,receivedfeedbackfrom10experts• VIMvalidationonlywith1expert
• Positivereactions• Couldseebenefitsoflargescaleviewpointevaluationforstreets• LikedvisuallinkingbetweenspatialviewandVIMvalues• MostpopularVIMwaslandmarkocclusion(Vienna)
• Wouldhaveliked• Attributetoindicateshapeofacandidate
KnownLimitations
• Opennessmetricnotclearformost• Usedepthtoquantifyvolumeofopenspaceoccludedbycandidate
• ExpandTRVtoother“hardcriteria”eg.Maxheight,min.floorspace,officetoapartmentratio,etc• VIMforshadowcastbycandidate• Movementprofilesofaviewpointeg.#peopleataviewpointpassingthrough
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Summary
• What:Data• Spatiallocationsofcandidatebuildings• VIMderivedmetrics
• How:Encode• Spatial3Dview->3Dmap• Non-spatialtransposablerankview->histograms,barcharts,stackedbarcharts
• How:Reduce• Elide(barheightchange)andfilteroptiontochosenfocusset
• Scale• 30candidatestested• Viewpointsproblematic->suggestedfurtherfilteringofviewpointswithlowcoveragetocompensate
• Morethan4VIMmetricscouldbepossible
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MyTake
• Whatitdidwell• Greatwillingnesstocarryoverdomaintechniquesforfamiliaritywithtargetusers• Likedhowtheyquantifiedaestheticinformationforeasiercomparison,ranking,andfiltering
• Gooduseoflinkingbetweenviewstounderstandacandidate/viewpointintermsofaVIM
• Improvements• Galleryviewforfilmstripinsteadofhorizontalstriparea(visuallycompareviewpointsmoreatonce)
• “History”featuresincefilteringwilleliminateprevioussteps,mayhavetogoback?• StrongerVIMmetricdefinitions->getmoreexperts• AbilitytodefineviewpointcoveragecriteriaorotherVIMmetricsfurther(mightbedifferentandcontextdependent)
• Figuresnotalwaysclear,especiallyfilter/transpose…hadtoconsultvideotorealize
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Thanksforwatching!
• Titleimages• http://www.wrirosscities.org/news/three-lessons-negotiating-urban-planning-process-embarq%E2%80%99s-city-building-exercise• http://archinect.com/dariomatteini/project/m-arch-in-projecting-and-urban-planning-dublin-docklands-new-masterplan
• DomainPracticeimages• http://dunster.ca/services/land-use-planning-services/examples-past-projects/• http://udv.lab.uic.edu/education/managingphotos/types.htm• http://www.world-architects.com/architektur-news/insight/On_Architectural_Models_2247• http://www.siliconoutsourcing.net/cad-design-drafting/architecture-rendering.html
• RelatedWorkimages• https://docs.unity3d.com/460/Documentation/Manual/OcclusionCulling.html• http://www.nationalgeographic.org/encyclopedia/geographic-information-system-gis/• P.vanderCorput andJ.J.vanWijk,"ICLIC:Interactivecategorizationoflargeimagecollections,"2016IEEEPacificVisualization
Symposium(PacificVis),Taipei,2016,pp.152-159.doi:10.1109/PACIFICVIS.2016.7465263URL:http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7465263&isnumber=7465233
• Remainingimagesarefrommainpaper
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