Evolutionary Image Transition Using Random Walks

  • Aneta NeumannEmail author
  • Bradley Alexander
  • Frank Neumann
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10198)


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.


Random Walk Transition Process Mutation Operator Target Image Deep Neural Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



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


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Aneta Neumann
    • 1
    Email author
  • Bradley Alexander
    • 1
  • Frank Neumann
    • 1
  1. 1.Optimisation and Logistics, School of Computer ScienceThe University of AdelaideAdelaideAustralia

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