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International Conference on Computational Intelligence in Music, Sound, Art and Design

EvoMUSART 2018: Computational Intelligence in Music, Sound, Art and Design pp 34–49Cite as

Non-photorealistic Rendering with Cartesian Genetic Programming Using Graphics Processing Units

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10783))

Abstract

A non-photorealistic rendering system implemented with Cartesian genetic programming (CGP) is discussed. The system is based on Baniasadi’s NPR system using tree-based GP. The CGP implementation uses a more economical representation of rendering expressions compared to the tree-based system. The system borrows their many-objective fitness evaluation scheme, which uses a model of aesthetics, colour testing, and image matching. GPU acceleration of the paint stroke application results in up to 6 times faster rendering times compared to CPU-based renderings. The convergence dynamics of CGP’s \(\mu +\lambda \) evolutionary strategy was more unstable than conventional GP runs with large populations. One possible reason may be the sensitivity of the smaller \(\mu +\lambda \) population to the many-objective ranking scheme, especially when objectives are in conflict with each other. This instability is arguably an advantage as an exploratory tool, especially when considering the subjectivity inherent in evolutionary art.

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Notes

  1. 1.

    http://www.cosc.brocku.ca/~bross/CGP_NPR/Gallery/.

  2. 2.

    https://en.wikipedia.org/wiki/GeForce_10_series.

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Acknowledgements

This research was supported by NSERC Discovery Grant RGPIN-2016-03653.

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Authors and Affiliations

  1. Department of Computer Science, Brock University, 1812 Sir Isaac Brock Way, St. Catharines, ON, L2S 3A1, Canada

    Illya Bakurov & Brian J. Ross

Authors
  1. Illya Bakurov
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  2. Brian J. Ross
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Correspondence to Brian J. Ross .

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Editors and Affiliations

  1. University of Malta , Msida , Malta

    Antonios Liapis

  2. University of A Coruña , A Coruña, Spain

    Juan Jesús Romero Cardalda

  3. Aston University , Birmingham, United Kingdom

    Anikó Ekárt

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Bakurov, I., Ross, B.J. (2018). Non-photorealistic Rendering with Cartesian Genetic Programming Using Graphics Processing Units. In: Liapis, A., Romero Cardalda, J., Ekárt, A. (eds) Computational Intelligence in Music, Sound, Art and Design. EvoMUSART 2018. Lecture Notes in Computer Science(), vol 10783. Springer, Cham. https://doi.org/10.1007/978-3-319-77583-8_3

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  • DOI: https://doi.org/10.1007/978-3-319-77583-8_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77582-1

  • Online ISBN: 978-3-319-77583-8

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