Non-photorealistic Rendering Using Genetic Programming

Authors:
Perry Barile;Vic Ciesielski;Karen Trist
Affiliations:
School of Computer Science and Information Technology, RMIT University, Melbourne, Australia 3000, VIC;School of Computer Science and Information Technology, RMIT University, Melbourne, Australia 3000, VIC;School of Computer Science and Information Technology, RMIT University, Melbourne, Australia 3000, VIC
Venue:
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
Year:
2008

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Abstract

We take a novel approach to Non-Photorealistic Rendering by adapting genetic programming in combination with computer graphics drawing techniques. As a GP tree is evaluated, upon encountering certain nodes referred to as "Draw" nodes, information contained within such nodes are sent to one of three virtual canvasses and a mark is deposited on the canvas. For two of the canvasses the user is able to define custom brushes to be applied to the canvas. Drawing functions are supplied with little localised information regarding the target image. Based on this local data, the drawing functions are enabled to apply contextualized information to the canvas. The obtained results include a "Shroud of Turin" effect, a "Decal" effect and a "Starburst" effect.