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Computer-Generated Watercolor

Computer-Generated Watercolor. Curtis, Anderson, Seims, Fleischer, & Salesin SIGGRAPH 1997 presented by Dave Edwards. Motivation. Trend toward nonphotorealistic rendering D. Small: Watercolor on a Connection Machine Commercial software Q. Guo & T. Kunii: Ink diffusion through paper

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Computer-Generated Watercolor

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  1. Computer-Generated Watercolor Curtis, Anderson, Seims, Fleischer, & Salesin SIGGRAPH 1997 presented by Dave Edwards

  2. Motivation • Trend toward nonphotorealistic rendering • D. Small: Watercolor on a Connection Machine • Commercial software • Q. Guo & T. Kunii: Ink diffusion through paper • Animating the fluid dynamics of water • Effects of water flow on surface appearance • Watercolor exhibits beauty & uniqueness

  3. Simulating Watercolor • Simulation based on • Physical nature of watercolor • Artistic effects of watercolor • Ultimate goal • Result of simulation should be realistic

  4. Watercolor Materials • Watercolor paint • Pigment particles • Binder • Surfactant • Watercolor paper • Linen or cotton • Sizing

  5. Watercolor Effects • Dry-brush • Paint applied to raised areas of paper Real Simulated

  6. Watercolor Effects • Edge Darkening • Pigment migrates toward edges of wet surface Real Simulated

  7. Watercolor Effects • Backruns • Spreading water moves pigment on damp surface Real Simulated

  8. Watercolor Effects • Granulation • More pigment settles in lower areas on paper Real Simulated

  9. Watercolor Effects • Flow Patterns • Wet paper allows pigment to spread freely Real Simulated

  10. Watercolor Effects • Glazing • Thin layers of new paint added atop old dry layers Real Simulated

  11. Simulation Overview • Image represented by 2-D grid of cells • Each brushstroke stored in glaze data struct • Stores pigment concentration per image cell • Software creates glazes by simulating • Fluid flow over paper • Pigment movement in fluid • Fluid diffusion through paper • Glazes combined into single image • Optical combination using Kubelka-Munk model

  12. Paper Representation • Paper attributes (per cell) • Height • Fluid capacity • Paper surface texture examples:

  13. Simulation Data • Store each of the following per cell: • Wet-area masks • Water velocity • Water pressure • Paper saturation • Pigment concentration • Free in water • Deposited on paper

  14. Watercolor Simulation • Three-layer model

  15. Watercolor Simulation • Simulate fluid & pigment movement in loop • Move water on surface of paper • Move pigment between cells • Adsorb pigment into paper & desorb into water • Expand wet portion of paper through diffusion • Repeat for each time step

  16. Water Movement • Conditions • Water stays within wet-area mask • Water should flow away from concentrated areas • Flow should be damped (no sloshing) • Flow should be affected by paper contours • Local changes lead to global effects • Flow toward edges (produce edge darkening)

  17. Pigment Movement • Based on • Water velocity • Free pigment concentration • Each cell distributes pigment to neighbors • Simplified equation: • vji = water velocity between cell j and cell i • pi = pigment concentration at cell i

  18. Adsorption & Desorption • Pigments deposited & picked up again • Rates based on global constants • Pigment density • Staining power • Can also be based on paper height • Granulation

  19. Diffusion & Effects • Backruns • Water absorbed and diffused through paper • Cells transfer diffused water to neighbors • Water saturation stored for each cell • Wet-area mask grows based on saturation threshold • Dry-brush • User can specify height mask

  20. Rendering a Simulation • Kubelka-Munk optical model • Glazes have absorption & scattering coefficients • One of each coefficient for R, G, and B • Specified interactively • User sets pigment color on white & black backgrounds • Coefficients calculated from these colors

  21. Pigment Examples • Swatches

  22. Compositing Glazes • Calculate glaze’s reflectance & transmittance • Based on absorption & scattering coefficients • Each value has an R, G, and B component • Calculate total reflectance & transmittance • Based on refl. & trans. from each glaze in cell • Glaze thickness is also taken into account • Sum of free & deposited pigment concentrations • Total reflectance values used to render cell

  23. Applications • “Interactive” painting • User specfies intial conditions for simulation • Water, wet-area mask, & pigment concentration • Height mask for dry-brush effects is optional • Simulation parameters can be changed • Can’t run simulation in real-time • Can calculate K-M model in real-time

  24. Applications • Automatic watercolorization • Based on digital reference image • User specifies pigments & object mattes • Color Separation • Software calculates ideal final pigment concentration • Brushstroke planning • Software adds water or pigment during simulation • Approximates original image with watercolor style • Also works for synthetic images

  25. Future Work • Additional watercolor effects • Completely automatic watercolorization • Generalization of physical effects • Animation coherence

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