Thomas Ortner, Johannes Sorger, Harald Steinlechner...

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


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b) Stackedbarchartiscompactrep.ofbarcharts




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c) Linkedpeekbrushingshowsdetailondemandandcurrentcandidateacrossotherviewpoints(letter)




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d) Anyrowthatisrankedbydistributionscoresoverallviewpoints




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e) Arrowiconloadsintospatialviewoftool(Map)




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e) Arrowiconloadsintospatialviewoftool(Map)

f) Ahighlevelsummaryofacategoryofviewpoint

ViewpointMajorModePop-outisforexample


TransposableRankingView(TRV)– Focus,Filter,TransposeWorkflowExample

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SelecthighimpactVIMportionacrossallviewpoints(CandidateVisibility)ofinterest


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Focused subsetnowemphasizedwithsplitheightenedbarcharts(left).Remainingdistributionloweredinheightforcontext (right).


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Canfocusagain.Canexpandarow(vp48)formoredetailedbarchart->exactcandidateVIMvalues


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Filter/transposeoptiononfocusedset

Usefilteroptionabovetoseefilteredviewpointdistributionsnow.Emphasizefocusedareaforinspection.


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Transposetoswitchrowordering

Aftertranspose,rowsnowshowpercandidate,viewpointbasedVIMdistributionsonfilteredset


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Canevenextendfocusedsettootherportionsofdistribution


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Resultofappendingtofocusedset


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Canfilteronappendedsubsettoseefocusedareainmoredetail


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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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