Comp 767: Advanced Topics in Graphics Comp 767: Advanced Topics in Graphics Computer-Generated Computer-Generated Watercolor Watercolor Cassidy J. Curtis Cassidy J. Curtis Sean E. Anderson Sean E. Anderson Kurt W. Fleischer Kurt W. Fleischer David H. Salesin David H. Salesin Irwin Chiu Hau Irwin Chiu Hau Computer Science Computer Science McGill University McGill University Winter 2004 Winter 2004
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Comp 767: Advanced Topics in Graphics Computer-Generated Watercolor Cassidy J. CurtisSean E. Anderson Kurt W. FleischerDavid H. Salesin Irwin Chiu Hau.
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Comp 767: Advanced Topics in Graphics Comp 767: Advanced Topics in Graphics
Cassidy J. CurtisCassidy J. Curtis Sean E. AndersonSean E. AndersonKurt W. FleischerKurt W. Fleischer David H. SalesinDavid H. Salesin
Irwin Chiu HauIrwin Chiu Hau
Computer ScienceComputer Science
McGill UniversityMcGill University
Winter 2004Winter 2004
OverviewOverview
IntroductionIntroductionProperties of watercolorProperties of watercolorComputer-generated watercolorComputer-generated watercolorApplicationsApplicationsFuture workFuture workConclusionConclusion
IntroductionIntroduction
What is watercolor painting?What is watercolor painting?Computer generated watercolor as Computer generated watercolor as
a non-photorealistic renderinga non-photorealistic rendering
OverviewOverview
IntroductionIntroductionProperties of watercolorProperties of watercolorComputer-generated watercolorComputer-generated watercolorApplicationsApplicationsFuture workFuture workConclusionConclusion
Granulation and Separation of Granulation and Separation of PigmentsPigments
Granulation of pigmentsGranulation of pigmentsYields a kind of grainy texturesYields a kind of grainy texturesVaries from pigment to Varies from pigment to
pigmentpigmentStrongest when paper is very Strongest when paper is very
wetwet
Separation of pigmentSeparation of pigment Refers to splitting of colorsRefers to splitting of colorsOccurs when denser pigments Occurs when denser pigments
settle earlier than lighter onessettle earlier than lighter onesSource:
Computer Generated Watercolor
Flow PatternsFlow Patterns
In wet-in-wet paintingIn wet-in-wet paintingwet surface allows the
brushstrokes to spread freely
EffectsEffectsSoft, feathery shapes
Source:
Computer Generated Watercolor
GlazingGlazing
TechniquesAdding very thin, pale layers,
or washes, of watercolor, one over another
Different pigments are not mixed physically, but optically
EffectsEffects luminousglowing from within
Source:
Computer Generated Watercolor
OverviewOverview
IntroductionIntroductionProperties of watercolorProperties of watercolorComputer-generated watercolorComputer-generated watercolorApplicationsApplicationsFuture workFuture workConclusionConclusion
Cellular AutomatonCellular AutomatonDefinition from Mathworld.comDefinition from Mathworld.com
A cellular automaton is a collection of A cellular automaton is a collection of "colored" cells on a grid of specified "colored" cells on a grid of specified shape that evolves through a number of shape that evolves through a number of discrete time steps according to a set of discrete time steps according to a set of rules based on the states of neighboring rules based on the states of neighboring cells cells
Game of Life
Source: Mathworld.com
Move WaterMove Water
proc MoveWater(M, u, v, p):UpdateVelocities(M, u, v, p)RelaxDivergence(M, u, v, p)FlowOutward(M, p)
end procedge darkening
M : wet-area masku, v : velocity
p : water pressure
Move PigmentMove Pigment
Pigments move within the shallow-water layer as specified by the velocity field u, v
Pigment from each cell are distributed to its neighbors at the rate of fluid movement out of the cell
Transfer PigmentTransfer Pigment
Pigment adsorption and desorptionPigment adsorption and desorption
proc TransferPigment(g 1, . . . ,g n,d 1, . . . ,d n ): for each pigment k do for all cells (i, j) do …
g, d : pigment concentrations
Source: Computer Generated Watercolor
Simulate Capillary FlowSimulate Capillary Flow
Diffusing water through the capillary layerproc SimulateCapillaryFlow(s, M ): for each pigment k do for all cells (i, j) do …
backruns
s : water saturation of the paper
dry-brush effects
Source: Computer Generated Watercolor
The Fluid SimulationThe Fluid Simulation
Main loop
proc MainLoop(M, u, v, p, g 1, … , g n, d 1, … , d n, s ):for each time step do:
MoveWater(M, u, v, p)MovePigment(M, u, v, g 1, … , g n)TransferPigment(g 1, … , g n, d 1, … , d n)SimulateCapillaryFlow(M, s)
end forend proc
initial wet-area mask
initial velocity
initial water pressure
initial pigment concentrations
initial water saturation of the paper
Optical compositingOptical compositingRendering the pigmented layers
Use the Use the Kubelka-Munk (KM) model to perform the optical compositing of glazing layers
Source: Computer Generated Watercolor
Kubelka-Munk (KM) Model
Comes from KM TheoryComes from KM Theory
Tells us how toTells us how tospecify the optical properties of specify the optical properties of
IntroductionIntroductionProperties of watercolorProperties of watercolorComputer-generated watercolorComputer-generated watercolorApplicationsApplicationsFuture workFuture workConclusionConclusion
ApplicationsApplications
Interactive painting with watercolorsInteractive painting with watercolorsAutomatic image “watercolorization”Automatic image “watercolorization”Non-photorealistic rendering of 3D Non-photorealistic rendering of 3D
modelsmodels
Interactive PaintingInteractive Painting
User createsUser createsGlazesGlazes
User adjustsUser adjustsBrush sizesBrush sizesPigmentsPigmentsWet-mask Wet-mask
Given a 3D geometric scene, we Given a 3D geometric scene, we automatically generate mattes isolating each object
These mattes are used as input to the watercolorization process
The user specifies the pigment choices and brushstroke planning
Non-Photorealistic Animation
Several frames from a non-photorealistic animation of moving clouds
Source: Computer Generated Watercolor
3D Scene Detail of one frame
OverviewOverview
IntroductionIntroductionProperties of watercolorProperties of watercolorComputer-generated watercolorComputer-generated watercolorApplicationsApplicationsFuture workFuture workConclusionConclusion
Future WorkFuture Work
Other effectsOther effectsAutomatic renderingAutomatic renderingGeneralizationGeneralizationAnimation IssuesAnimation Issues
OverviewOverview
IntroductionIntroductionProperties of watercolorProperties of watercolorComputer-generated watercolorComputer-generated watercolorApplicationsApplicationsFuture workFuture workConclusionConclusion
Cassidy J. Curtis, Sean E. Anderson,Cassidy J. Curtis, Sean E. Anderson,Kurt W. Fleischer and David H. Salesin. Kurt W. Fleischer and David H. Salesin. Computer-Generated WatercolorComputer-Generated Watercolor