Paint by numbers: abstract image representations
SIGGRAPH '90 Proceedings of the 17th annual conference on Computer graphics and interactive techniques
Artificial evolution for computer graphics
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Genetic programming: on the programming of computers by means of natural selection
Genetic programming: on the programming of computers by means of natural selection
Computer-generated pen-and-ink illustration
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Applied Intelligence
Tutorial: A Survey of Stroke-Based Rendering
IEEE Computer Graphics and Applications
3D Computer Graphics: A Mathematical Introduction with OpenGL
3D Computer Graphics: A Mathematical Introduction with OpenGL
IMPaSTo: a realistic, interactive model for paint
Proceedings of the 3rd international symposium on Non-photorealistic animation and rendering
MoXi: real-time ink dispersion in absorbent paper
ACM SIGGRAPH 2005 Papers
Probabilistic silhouette based importance toward line-art non-photorealistic rendering
The Visual Computer: International Journal of Computer Graphics
Evolving Virtual Creatures and Catapults
Artificial Life
Curvature-based stroke rendering
The Visual Computer: International Journal of Computer Graphics
The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music (Natural Computing Series)
The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music (Natural Computing Series)
Genetic paint: a search for salient paintings
EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Animations rendered by braitenberg vehicles
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
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We describe an approach to generating animations of drawings that start as a random collection of strokes and gradually resolve into a recognizable subject. The strokes are represented as tree based genetic programs. An animation is generated by rendering the best individual in a generation as a frame of a movie. The resulting animations have an engaging characteristic in which the target slowly emerges from a random set of strokes. We have generated two qualitatively different kinds of animations, ones that use grey level straight line strokes and ones that use binary Bezier curve stokes. Around 100,000 generations are needed to generate engaging animations. Population sizes of 2 and 4 give the best convergence behaviour. Convergence can be accelerated by using information from the target in drawing a stroke. Our approach provides a large range of creative opportunities for artists. Artists have control over choice of target and the various stroke parameters.