Evolutionary Image Transition Using Random Walks

被引:15
作者
Neumann, Aneta [1 ]
Alexander, Bradley [1 ]
Neumann, Frank [1 ]
机构
[1] Univ Adelaide, Sch Comp Sci, Optimisat & Logist, Adelaide, SA, Australia
来源
COMPUTATIONAL INTELLIGENCE IN MUSIC, SOUND, ART AND DESIGN, EVOMUSART 2017 | 2017年 / 10198卷
基金
澳大利亚研究理事会;
关键词
ALGORITHMS; SEARCH; BOUNDS; TIME;
D O I
10.1007/978-3-319-55750-2_16
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:230 / 245
页数:16
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