Rendering Complexity in Computer-Generated Pen-and-Ink Illustrations

Rendering Complexity in Computer-Generated

Pen-and-Ink Illustrations

Brett Wilson & Kwan-Liu Ma

The University of California, Davis

How would an artist treat this scene?

• Ambiguous boundaries

• Ambiguous depth

Method 1: Abstraction

• Merge similar regions

• Strokes don’t followgeometry exactly

• Good color / texture

Method 2: Separation

• Separate similar regions

• Geometry is clear

• Color is not as true

How can a computermake these decisions?

• Introduction to NPR pipelines

• Hybrid 2D / 3D pipeline

• Abstraction: when and how?– Silhouette rendering– Hatching

Image-based NPR

• Good abstraction• Low detail — always lose information

Image Image

Geometry-based NPR

• Poor abstraction• High detail — gain information

Geometry Image

Geometry rendering techniques

• Hierarchical textures [Winkenbach & Salesin 1994]

• Arbitrary meshes [Girshick et al. 2000]

• Smoothed direction fields [Hertzmann & Zorin 2000]

Neither of these techniquesworks well for complex scenes.

• 2D approach gives too little detail, no relative importance

• 3D approach gives too much detail, hard to pick out important things

• Challenge: Intelligent use of abstraction

2+D NPR processing

• Hamel & Strothotte: Capturing and Re-Using Rendering Styles for NPR [EG ’99]

• Generate multiple renderings• Match image attributes to example

input

• Discard geometry

Tree rendering.

• Deussen & Strothotte: Computer-Generated Pen-and-Ink Illustrations of Trees [SIGGRAPH 2000]

• Generate 2D depth renderings to extract important feature lines of the foliage.

• Requires complex areas (leaves) to be tagged.

A generalized hybrid pipeline.

• Add rendering and segmentation to the middle of the pipeline.

Silhouette rendering

• Generate a complexity map

• Indicates regions of high geometric complexity

• Simplify areas likely to be confusing

A complexity map generatedfrom an edge rendering.Silhouette rendering Complexity map

• Many other ways to measure complexity

Silhouette image should match a grayscale rendering.

Edges Target

Too light Too dark

Resulting edge rendering

• Use Deussen’s technique to keep edges in order of importance

• Add occluded edgesfor darkening

Grayscale rendering with hatching.

• Artists don’t draw every object with separate strokes

• Small, similar objects grouped and use the same strokes

• Apply based on complexity

Segmentation for hatching

• Use segmentation to identify groups of strokes.

– Depth– Angle

– Color– Texture– …etc.

Notes on segmentation.

• Much easier than general image segmentation

• No image understanding necessary

• Simple segmentation is acceptable– Region growing

Segmentation-based hatching with important silhouette lines.

Primate Chest Isosurface

• 3.5 M triangles

• High detail

• Ambiguous area

Silhouette edges

Fully hatched rendering

The rendering is separated into complex and non-complex regions.

Simple Complex

Hybrid pen/paint rendering

• Hatching fornon-complex areas

• Solid black shadingfor complex areas

• Preserves feel whilesimplifying rendering

Close-up comparison of hybrid rendering

Sharp boundaries

• Blur operationaffects boundaries

• “Knock out” large objects

• Future work:Clustering in Z?

Conclusion

• Abstraction– When– How

• How will the viewer perceive the scene?– Incorporate segmentation in 3D pipeline

• Clearer, more artistically believable pictures

Future work

• Better models

• Higher-quality hatching

• More rendering styles in general

• More possibilities with segmentation

Thank You

• Funded by the U.S. National Science Foundation under– ACI 9983641 (PECASE

award)– ACI 0325934 (ITR)– ACI 0222991