Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/111307
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Type: Conference paper
Title: Evolutionary image transition using random walks
Author: Neumann, A.
Alexander, B.
Neumann, F.
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: Springer
Publisher Place: Cham, Switzerland
Issue Date: 2017
Series/Report no.: Lecture Notes in Computer Science; 10198
ISBN: 3319557491
9783319557496
ISSN: 0302-9743
1611-3349
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)
Statement of
Responsibility: 
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
RMID: 0030068925
DOI: 10.1007/978-3-319-55750-2_16
Grant ID: http://purl.org/au-research/grants/arc/DP140103400
Published version: http://www.springer.com/gp/book/9783319557496
Appears in Collections:Computer Science publications

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