Abstract
We have developed a method for generating non photorealistic animations of a target image. The animations start as a random collection of triangular strokes on a canvas and the target gradually emerges as the animation proceeds. We use genetic programming to evolve programs that draw the brushstrokes. A measure of similarity to the target is used as the fitness function. The best individual in a generation becomes a frame of the animation. We have experimented with open and filled triangles. Both kinds of triangles resulted in animations that our artist collaborators found engaging and interesting. In particular, the use of filled triangles generated animations that exhibited a novel immersive quality. The evolutionary approach requires artistic judgment in selecting the target images and values for the various parameters and provides a rich environment for exploring novel non photo–realistic renderings.
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Izadi, A., Ciesielski, V., Berry, M. (2010). Evolutionary Non Photo–Realistic Animations with Triangular Brushstrokes. In: Li, J. (eds) AI 2010: Advances in Artificial Intelligence. AI 2010. Lecture Notes in Computer Science(), vol 6464. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17432-2_29
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DOI: https://doi.org/10.1007/978-3-642-17432-2_29
Publisher Name: Springer, Berlin, Heidelberg
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