1 / 35

Paint By Numbers : Abstract Image Representation

Paint By Numbers : Abstract Image Representation Paul Haeberli Silicon Graphics Computer Systems ACM SIGGRAPH Computer graphics Proceeding of 17 th , 1990 Outline Motivation Overview Painting Techniques Stroke Attributes Operations on Paintings Advanced Techniques Spice for Images

Gabriel
Download Presentation

Paint By Numbers : Abstract Image Representation

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Paint By Numbers : Abstract Image Representation Paul Haeberli Silicon Graphics Computer Systems ACM SIGGRAPH Computer graphics Proceeding of 17th, 1990

  2. Outline • Motivation • Overview • Painting Techniques • Stroke Attributes • Operations on Paintings • Advanced Techniques • Spice for Images • Conclusion • Further work

  3. Motivation

  4. Motivation • Producing images indistinguishable from photograph • Graphic designer’s choice • Photorealistic, Not always the best choice • “How much use is a photograph to mechanics when they already have the real thing on front of them?”[Lansdown and Schofield] • Visual effect intended by designer [Lansdown and Schofield] J.Lansdown and S.Schofield. Expressive rendering: A review of nonphotorealistic techniques. IEEE ComputerGraphics and Applications, 1995.

  5. Overview

  6. Overview • Alternative to photorealism • Painterly rendering • Creation of artistic, stylized and abstract images • Impressionistic painting • Brush stroke control • User interactive system

  7. Painting Techniques

  8. Operation • Information from source image • Cursor across the canvas • Sampling color from image • Paint a brush stroke • Location • Color • Size • Direction • Shape

  9. Painting Example

  10. Stroke Location • Stochastic distribution around cursor • Example of interactive particle system[Reeves] [Reeves] William T. Reeves and Ricki Blau, “Approximate and probabilistic algorithm for shading and rendering structured particle systems”, Computer Graphics, 1985.

  11. Stroke Color • RGB and alpha value • Time limitation to pick new color • “put-that-color-there” procedure[Lewis] • Restrict to small number of color [Lewis] John-Peter Lewis, “Texture Synthesis for Digital Painting”, Computer Graphics, 1984.

  12. Stroke Size and Orientation • Size • Control by cursor speed • Easy to create rough representation • Control by arrow keys • Orientation • Direction of cursor • Mouse gesture • Image gradient

  13. Stroke Shape • Shape • Significant influenceto final painting • Circle, rectangle, line,scattering of points,polygon, cone, user-defined shape

  14. Painting Example Diagonal stroke Pointillist representation

  15. Painting Example • • Cone shape brush • • Voronoi diagram polygon resterizing hardware• rendering of cones to construct 2D Voronoi diagrams of points Cone shape

  16. Operations on paintings

  17. Painting Description • Painting as an ordered set of strokes • Containing stroke information • Operations on paintings • Transform painting into RGB images • Unary operation – scaling, sorting, adding noise, etc. • Binary operation – interpolation, extrapolation, animation, etc

  18. Description Table

  19. Advanced Techniques

  20. Brush Direction • Brush direction using second image

  21. Edge drawing • Edge drawing using luminance gradient

  22. Texture mapping • Brush texture mapping

  23. Sampling Geometry • Sampling geometry using Ray-tracing

  24. Approximation • Approximation using Relaxation

  25. Spice for images

  26. Edge enhancement • “Pushing edge” • More explicit depth relationship • Using unsharp masking

  27. Color enhancement • Increase saturation • Lum = 0.3*R + 0.59*G + 0.11*B • Extrapolation

  28. Color restriction and Background Color • Color restriction • Limited color for overall harmony and unity • Color quantization of source image • Noise for no contouring • Background cover • Unity and integrity • Color perception

  29. Conclusion

  30. Conclusion • A system for producing abstract image • The first experiment on NPR • Making stylized abstract image • Interactive processing • Motivations for future works • Media • Method

  31. Advanced Work

  32. Inspiration • Haeberli’s work • The first work on NPR • Some issues • Stroke methods, attributes, animation, etc • After Haeberli’s work • Considerable works on painting system • Two large categorization • Digital analogues • Automatic stroke

  33. Digital analogues • Salisbury et al. 1994 • Pen and ink • Curtis et al. 1997 • Watercolor • Sousa et al. 1999 • Pencil drawing

  34. Automatic stroke • Litwinowicz, 1997 • Hertzmann, 1998 • Shiraishi and Yamaguchi, 2000 • Only global effect by user • Brush size or shape

  35. Stroke Dimension • Dana, 1996 • 8D dimension for social visualization[Dana] • To show social data Animation • Meier, 1996 • Using particle rendering methods

More Related