Computer-Generated Watercolor

1
Computer-Generated Watercolor

• Cassidy J. Curtis
• Sean E. Anderson
• Joshua E. Seims
• Kurt W. Fleischer
• David H. Salesin

2
Outline

• Introduction
• Related work
• Background
• Overview
• Watercolor simulation
• Rendering
• Applications
• Results
• Conclusion

3
Introduction

• Various artistic effects of watercolor

4
Related work

• Simulating artists traditional media and tools
• Watercolor David Small 1991
• Sumie Guo and Kunii 1991
• Commercial package
• Fractal Design Painter

5
Background

• Properties of watercolor
• Watercolor paper
• Pigment
• Binder
• Surfactant

6
Background

• Watercolor Effects
• a) dry-brush
• b) Edge darkening
• c) Backruns
• d) granulation and separation of pigments
• e) Flow patterns
• f) color glazing

7
Overview

• Computer-generated watercolor
• 1. Fluid (and pigment) simulation for each glaze
• 2. Rendering

Glaze physical properties, area
8
Fluid simulation

• Three-layer model

9
Fluid simulation

• Paper Generation
• Height field model ( 0 lt h lt 1 )
• Based on pseudo-random process
• Fluid capacity c proportional to h

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Fluid simulation

• Main loop

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Fluid simulation

• Main loop

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Moving water

• conditions of water
• 1. To remain within the wet-area mask
• 2. To flow outward into nearby region
• 3. To be damped to minimize oscillating waves
• 4. To be perturbed by the texture of the paper
• 5. To be affected by local changes
• 6. To present the edge-darkening effect

13
Fluid simulation

• Configuration
• Staggered grid

i,j
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Fluid simulation

• Updating the water velocities
• Governing Equation (2D Navier-Stoke Eqn.)

15
Fluid simulation

• Derivation of Navier-Stoke Eqn.(1/5)
• Basic Eqn.
• For unit volume

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Fluid simulation

• Derivation of Navier-Stoke Eqn.(2/5)
• Two kind of measurements

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Fluid simulation

• Derivation of Navier-Stoke Eqn.(3/5)
• Eulerian view

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Fluid simulation

• Derivation of Navier-Stoke Eqn.(4/5)
• Governing Eq.
• Forces
• Gravity
• Viscosity
• Pressure

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Fluid simulation

• Derivation of Navier-Stoke Eqn.(5/5)
• Navier-Stoke Eqn.
• For 2D case,

20
Fluid simulation

• Updating the water velocities
• Numerical integration for u

21
Fluid simulation

• Updating the water velocities
• Applying paper slope effect
• Applying Drag Force

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Fluid simulation

• Mass conservation (1/3)
• Divergence free condition

23
Fluid simulation

• Mass conservation (2/3)
• Relaxation (iterative procedure)

24
Fluid simulation

• Mass conservation (3/3)
• Relaxation (iterative procedure)

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Fluid simulation

• Edge darkening
• To flow outward
• Remove some water at the boundary

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Fluid simulation

• Edge darkening

dry
wet
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Fluid simulation

• Main loop

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Fluid simulation

• Moving Pigments
• To move as specified by the velocity field u,v

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Fluid simulation

• Moving Pigments
• To move as specified by the velocity field u,v

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Fluid simulation

• Main loop

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Fluid simulation

• Transferring Pigments
• Adsorption and desorption

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Fluid simulation

• Main loop

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Fluid simulation

• Backruns
• Diffusing water through the capillary layer
• Spreading slowly into a drying region
• Transfer water to its dryer neighbors until they
  are saturated

34
Fluid simulation

• Drybrush effect
• By excluding any lower pixel than threshold

35
Rendering

• Optical properties of pigments
• Optical composition subtractive color mixing

36
Rendering

• Optical properties of pigments
• Kubelka-Munk (KM) Model
• To compute Reflectance R and Transmittance T
  using K and S

unit length
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Rendering

• Optical properties of pigments
• Kubelka-Munk (KM) Model

38
Rendering

• Optical properties of pigments
• Kubelka-Munk (KM) Model
• For multiple layers

39
Rendering

• Optical properties of pigments
• Kubelka-Munk (KM) Model

We need S and K values
Make user choose them intuitively
40
Rendering

• Optical properties of pigments
• User selects Rw and Rb

41
Rendering

• Optical properties of pigments
• User selects Rw and Rb

42
Applications

• 1. Interactive painting with watercolors
• 2. Automatic image watercolorization
• 3. Non-photorealistic rendering of 3D models

43
Applications

• 1. Interactive painting with watercolors

44
Applications

• 2. Automatic image watercolorization
• Color separation
• Brushstroke Planning

45
Applications

• 2. Automatic image watercolorization
• Color separation
• Determine the thickness of each pigment by
  brute-force search for all color combinations

46
Applications

• 2. Automatic image watercolorization
• Brushstroke planning

47
Applications

• 3. Non-photorealistic rendering of 3D models
• Using photorealistic scene of 3D model

48
Results
49
Results
50
Results
51
Results
52
Conclusion

• Various artistic effects of watercolor
• Water and pigment simulation
• Pigment Rendering
• Application
• Interactive system
• Automatic watercolorization of 2D and 3D

53
Further work

• Other effects
• Spattering and drybrush
• Automatic rendering
• Applying automatic recognition
• Generalization
• Integration of Wet-in-wet and backruns
• Animation issues
• Reducing temporal artifacts