research-article

Animated drawings rendered by genetic programming

Authors:

Vic Ciesielski,

Karen TristAuthors Info & Claims

GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation

Pages 939 - 946

https://doi.org/10.1145/1569901.1570030

Published: 08 July 2009 Publication History

Abstract

We describe an approach to generating animations of drawings that start as a random collection of strokes and gradually resolve into a recognizable subject. The strokes are represented as tree based genetic programs. An animation is generated by rendering the best individual in a generation as a frame of a movie. The resulting animations have an engaging characteristic in which the target slowly emerges from a random set of strokes. We have generated two qualitatively different kinds of animations, ones that use grey level straight line strokes and ones that use binary Bezier curve stokes. Around 100,000 generations are needed to generate engaging animations. Population sizes of 2 and 4 give the best convergence behaviour. Convergence can be accelerated by using information from the target in drawing a stroke. Our approach provides a large range of creative opportunities for artists. Artists have control over choice of target and the various stroke parameters.

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Cited By

Herrera-Sánchez DAcosta-Mesa HMezura-Montes EMárquez-Grajales ALi XHandl J(2024)Shifting Color Space for Image Classification using Genetic ProgrammingProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3638530.3654430(283-286)Online publication date: 14-Jul-2024
https://dl.acm.org/doi/10.1145/3638530.3654430
Adamik MGoga JPavlovicova JBabinec ASekaj I(2022)Fast robotic pencil drawing based on image evolution by means of genetic algorithmRobotics and Autonomous Systems10.1016/j.robot.2021.103912148:COnline publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1016/j.robot.2021.103912
Wu T(2018)Image-Guided Rendering with an Evolutionary Algorithm Based on Cloud ModelComputational Intelligence and Neuroscience10.1155/2018/45182652018Online publication date: 19-Feb-2018
https://dl.acm.org/doi/10.1155/2018/4518265
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Index Terms

Animated drawings rendered by genetic programming
1. Computing methodologies
  1. Computer graphics

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cover image ACM Conferences

GECCO '09: Proceedings of the 11th Annual conference on Genetic and evolutionary computation

July 2009

2036 pages

ISBN:9781605583259

DOI:10.1145/1569901

General Chair:
Franz Rothlauf
University of Mainz, Germany

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 08 July 2009

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GECCO09: Genetic and Evolutionary Computation Conference

July 8 - 12, 2009

Québec, Montreal, Canada

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Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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Cited By

Herrera-Sánchez DAcosta-Mesa HMezura-Montes EMárquez-Grajales ALi XHandl J(2024)Shifting Color Space for Image Classification using Genetic ProgrammingProceedings of the Genetic and Evolutionary Computation Conference Companion10.1145/3638530.3654430(283-286)Online publication date: 14-Jul-2024
https://dl.acm.org/doi/10.1145/3638530.3654430
Adamik MGoga JPavlovicova JBabinec ASekaj I(2022)Fast robotic pencil drawing based on image evolution by means of genetic algorithmRobotics and Autonomous Systems10.1016/j.robot.2021.103912148:COnline publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1016/j.robot.2021.103912
Wu T(2018)Image-Guided Rendering with an Evolutionary Algorithm Based on Cloud ModelComputational Intelligence and Neuroscience10.1155/2018/45182652018Online publication date: 19-Feb-2018
https://dl.acm.org/doi/10.1155/2018/4518265
Wu T(2018)Saliency-aware Generative ArtProceedings of the 2018 10th International Conference on Machine Learning and Computing10.1145/3195106.3195143(198-202)Online publication date: 26-Feb-2018
https://dl.acm.org/doi/10.1145/3195106.3195143
Zamuda AMlakar U(2016)Tiled EvoLisa image evolution with blending triangle brushstrokes and gene compression DE2016 IEEE Congress on Evolutionary Computation (CEC)10.1109/CEC.2016.7744116(2618-2625)Online publication date: Jul-2016
https://doi.org/10.1109/CEC.2016.7744116
Klapaukh RBrowne WZhang M(2013)The effect of primitive sets on the expression of evolved images2013 IEEE Congress on Evolutionary Computation10.1109/CEC.2013.6557640(725-732)Online publication date: Jun-2013
https://doi.org/10.1109/CEC.2013.6557640
Zamuda ABrest J(2012)Tree model reconstruction innovization using multi-objective differential evolution2012 IEEE Congress on Evolutionary Computation10.1109/CEC.2012.6256413(1-8)Online publication date: Jun-2012
https://doi.org/10.1109/CEC.2012.6256413
Ciesielski VBarile PLanzi P(2011)Animations rendered by braitenberg vehiclesProceedings of the 13th annual conference companion on Genetic and evolutionary computation10.1145/2001858.2001864(9-10)Online publication date: 12-Jul-2011
https://dl.acm.org/doi/10.1145/2001858.2001864

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