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Genetic paint: A search for salient paintings


Reference:

Collomosse, J. P. and Hall, P. M., 2005. Genetic paint: A search for salient paintings. In: Applications of Evolutionary Computing, Proceedings. Vol. 3449. , pp. 437-447. (Lecture Notes in Computer Science)

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Abstract

The contribution of this paper is a novel non-photorealistic rendering (NPR) algorithm for rendering real images in an impasto painterly style. We argue that figurative artworks are salience maps, and develop a novel painting algorithm that uses a genetic algorithm (GA) to search the space of possible paintings for a given image, so approaching an "optimal" artwork in which salient detail is conserved and non-salient detail is attenuated. We demonstrate the results of our technique on a wide range of images, illustrating both the improved control over level of detail due to our salience adaptive painting approach, and the benefits gained by subsequent relaxation of the painting using the GA.

Details

Item Type Book Sections
CreatorsCollomosse, J. P.and Hall, P. M.
DepartmentsFaculty of Science > Computer Science
StatusPublished
ID Code5417
Additional InformationID number: ISI:000229211900044

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