Genetic Paint: A Search for Salient Paintings

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Collomosse, John; Peter M. Hall Hall, Peter M.: Genetic Paint: A Search for Salient Paintings. In: EvoMUSART 2005, S. 437-447.



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.

Extended Abstract


booktitle={Applications of Evolutionary Computing},
series={Lecture Notes in Computer Science},
editor={Rothlauf, Franz and Branke, Jürgen and Cagnoni, Stefano and Corne, DavidWolfe and Drechsler, Rolf and Jin, Yaochu and Machado, Penousal and Marchiori, Elena and Romero, Juan and Smith, GeorgeD. and Squillero, Giovanni},
title={Genetic Paint: A Search for Salient Paintings},
url={ },
publisher={Springer Berlin Heidelberg},
author={Collomosse, J.P. and Hall, P.M.},

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