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|Title:||Evolutionary image transition using random walks|
|Citation:||Proccedings of the 6th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART 2017), 2017 / vol.10198 LNCS, pp.230-245|
|Publisher Place:||Cham, Switzerland|
|Series/Report no.:||Lecture Notes in Computer Science; 10198|
|Conference Name:||6th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART 2017) (19 Apr 2017 - 21 Apr 2017 : Amsterdam, The Netherlands)|
|Aneta Neumann, Bradley Alexander, and Frank Neumann|
|Abstract:||We present a study demonstrating how random walk algo- rithms can be used for evolutionary image transition. We design differ- ent 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 evolu- tionary image transition behaviour with respect to different features and evaluate the images constructed during the image transition process.|
|Description:||Also part of the Theoretical Computer Science and General Issues book sub series (LNTCS, volume 10198)|
|Rights:||© Springer International Publishing AG 2017|
|Appears in Collections:||Computer Science publications|
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