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Evolutionary Image Transition Using Random Walks

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Book cover Computational Intelligence in Music, Sound, Art and Design (EvoMUSART 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10198))

Abstract

We present a study demonstrating how random walk algorithms can be used for evolutionary image transition. We design different mutation operators based on uniform and biased random walks and study how their combination with a baseline mutation operator can lead to interesting image transition processes in terms of visual effects and artistic features. Using feature-based analysis we investigate the evolutionary image transition behaviour with respect to different features and evaluate the images constructed during the image transition process.

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Notes

  1. 1.

    Images and videos are available at https://vimeo.com/anetaneumann.

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Acknowledgement

This work has been supported through Australian Research Council (ARC) grant DP140103400.

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Authors and Affiliations

  1. Optimisation and Logistics, School of Computer Science, The University of Adelaide, Adelaide, Australia

    Aneta Neumann, Bradley Alexander & Frank Neumann

Authors
  1. Aneta Neumann
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  2. Bradley Alexander
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  3. Frank Neumann
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Corresponding author

Correspondence to Aneta Neumann .

Editor information

Editors and Affiliations

  1. University of Coimbra , Coimbra, Portugal

    João Correia

  2. RMIT University , Melbourne, Victoria, Australia

    Vic Ciesielski

  3. University of Malta , Msida, Malta

    Antonios Liapis

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Neumann, A., Alexander, B., Neumann, F. (2017). Evolutionary Image Transition Using Random Walks. In: Correia, J., Ciesielski, V., Liapis, A. (eds) Computational Intelligence in Music, Sound, Art and Design. EvoMUSART 2017. Lecture Notes in Computer Science(), vol 10198. Springer, Cham. https://doi.org/10.1007/978-3-319-55750-2_16

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  • DOI: https://doi.org/10.1007/978-3-319-55750-2_16

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  • Online ISBN: 978-3-319-55750-2

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