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Computer-Generated Watercolor

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Presentation on theme: "Computer-Generated Watercolor"— Presentation transcript:

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 < h < 1 ) Based on pseudo-random process Fluid capacity c: proportional to h

10 Fluid simulation Main loop Moving Water Moving Pigments
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments For each time step

11 Fluid simulation Main loop Moving Water Moving Pigments
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments For each time step

12 Moving water conditions of water 1. To remain within the wet-area mask
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments 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 Navier-Stoke Eq. Viscous drag k Paper slope h Mass conserv. Flow outward

13 Fluid simulation Configuration Staggered grid i,j Moving Water
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Configuration Staggered grid i,j

14 Fluid simulation Updating the water velocities
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Updating the water velocities Governing Equation (2D Navier-Stoke Eqn.)

15 Fluid simulation Derivation of Navier-Stoke Eqn.(1/5) Basic Eqn.:
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Derivation of Navier-Stoke Eqn.(1/5) Basic Eqn.: For unit volume:

16 Fluid simulation Derivation of Navier-Stoke Eqn.(2/5)
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Derivation of Navier-Stoke Eqn.(2/5) Two kind of measurements fluid solid Control volume

17 Fluid simulation Derivation of Navier-Stoke Eqn.(3/5) Eulerian view
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Derivation of Navier-Stoke Eqn.(3/5) Eulerian view

18 Fluid simulation Derivation of Navier-Stoke Eqn.(4/5) Governing Eq.:
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Derivation of Navier-Stoke Eqn.(4/5) Governing Eq.: Forces: Gravity: Viscosity: Pressure:

19 Fluid simulation Derivation of Navier-Stoke Eqn.(5/5)
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Derivation of Navier-Stoke Eqn.(5/5) Navier-Stoke Eqn. For 2D case,

20 Fluid simulation Updating the water velocities
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Updating the water velocities Numerical integration for u

21 Fluid simulation Updating the water velocities
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Updating the water velocities Applying paper slope effect: Applying Drag Force:

22 Fluid simulation Mass conservation (1/3) Divergence free condition
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Mass conservation (1/3) Divergence free condition

23 Fluid simulation Mass conservation (2/3)
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Mass conservation (2/3) Relaxation (iterative procedure)

24 Fluid simulation Mass conservation (3/3)
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Mass conservation (3/3) Relaxation (iterative procedure)

25 Fluid simulation Edge darkening To flow outward
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Edge darkening To flow outward Remove some water at the boundary

26 Fluid simulation Edge darkening dry wet 1 M .1 .4 .6 1 .9 M’ .4 .1
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Edge darkening dry wet 1 M .1 .4 .6 1 .9 M’ .4 .1 (1-M’)M

27 Fluid simulation Main loop Moving Water Moving Pigments
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments For each time step

28 Fluid simulation Moving Pigments
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Moving Pigments To move as specified by the velocity field u,v

29 Fluid simulation Moving Pigments
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Moving Pigments To move as specified by the velocity field u,v

30 Fluid simulation Main loop Moving Water Moving Pigments
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments For each time step

31 Fluid simulation Transferring Pigments Adsorption and desorption
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments Transferring Pigments Adsorption and desorption Adsorption Desorption

32 Fluid simulation Main loop Moving Water Moving Pigments
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments For each time step

33 Fluid simulation Backruns Diffusing water through the capillary layer
Applying Capillary Flow Moving Water Moving Pigments Transferring Pigments 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 S K Optical properties of pigments Kubelka-Munk (KM) Model
To compute Reflectance R and Transmittance T using K and S backscattered S unit length absorbed K

37 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 We need S and K values
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 Application
Water and pigment simulation Pigment Rendering Application Interactive system Automatic “watercolorization” of 2D and 3D

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


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