Non-photorealistic Rendering Using Genetic Programming
Inhaltsverzeichnis
Reference
Perry Barile and Victor Ciesielski and Karen Trist: Non-photorealistic Rendering Using Genetic Programming. Proceedings of the 7th International Conference on Simulated Evolution And Learning (SEAL '08), Lecture Notes in Computer Science, Vol. 5361, pp. 299-308, Springer, December 7-10 2008.
DOI
http://dx.doi.org/10.1007/978-3-540-89694-4_31
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.
Extended Abstract
Bibtex
Used References
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