Treffer: Supervised genetic search for parameter selection in painterly rendering

Title:
Supervised genetic search for parameter selection in painterly rendering
Authors:
COLLOMOSSE, John P
Source:
Applications of evolutionary computing (EvoWorkshops 2006)Lecture notes in computer science. :599-610
Publisher Information:
Berlin: Springer, 2006.
Publication Year:
2006
Physical Description:
print, 24 ref 1
Original Material:
INIST-CNRS
Subject Terms:
Bioinformatics, Bioinformatique, Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Algorithmique. Calculabilité. Arithmétique ordinateur, Algorithmics. Computability. Computer arithmetics, Intelligence artificielle, Artificial intelligence, Algorithme génétique, Genetic algorithm, Algoritmo genético, Algorithme évolutionniste, Evolutionary algorithm, Algoritmo evoluciónista, Analyse multirésolution, Multiresolution analysis, Análisis multiresolución, Esthétique, Aesthetics, Estética, Faisabilité, Feasibility, Practicabilidad, Peinture(art), Painting (art), Pintura(arte), Système expert, Expert system, Sistema experto
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Computer Science, University of Bath, Bath, United Kingdom
ISSN:
0302-9743
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=19131295
Rights:
Copyright 2007 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.19131295
Database:
PASCAL Archive

Weitere Informationen

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.