Supervised Genetic Search for Parameter Selection in Painterly Rendering
Inhaltsverzeichnis
Reference
Collomosse, John: Supervised Genetic Search for Parameter Selection in Painterly Rendering. In: EvoMUSART 2006, S. 599-610.
DOI
http://link.springer.com/10.1007/11732242_57
Abstract
This paper investigates the feasibility of evolutionary search techniques as a mechanism for interactively exploring the design space of 2D painterly renderings. Although a growing body of painterly rendering literature exists, the large number of low-level configurable parameters that feature in contemporary algorithms can be counter-intuitive for non-expert users to set. In this paper we first describe a multi-resolution painting algorithm capable of transforming photographs into paintings at interactive speeds. We then present a supervised evolutionary search process in which the user scores paintings on their aesthetics to guide the specification of their desired painterly rendering. Using our system, non-expert users are able to produce their desired aesthetic in approximately 20 mouse clicks — around half an order of magnitude faster than manual specification of individual rendering parameters by trial and error.
Extended Abstract
Bibtex
@incollection{
year={2006},
isbn={978-3-540-33237-4},
booktitle={Applications of Evolutionary Computing},
volume={3907},
series={Lecture Notes in Computer Science},
editor={Rothlauf, Franz and Branke, Jürgen and Cagnoni, Stefano and Costa, Ernesto and Cotta, Carlos and Drechsler, Rolf and Lutton, Evelyne and Machado, Penousal and Moore, JasonH. and Romero, Juan and Smith, GeorgeD. and Squillero, Giovanni and Takagi, Hideyuki},
doi={10.1007/11732242_57},
title={Supervised Genetic Search for Parameter Selection in Painterly Rendering},
url={http://dx.doi.org/10.1007/11732242_57 http://de.evo-art.org/index.php?title=Supervised_Genetic_Search_for_Parameter_Selection_in_Painterly_Rendering },
publisher={Springer Berlin Heidelberg},
author={Collomosse, JohnP.},
pages={599-610},
language={English}
}
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