Using Physiological Signals to Evolve Art

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Basa, Tristan; Go, Christian Anthony; Yoo, Kil-Sang; Lee, Won-Hyung: Using Physiological Signals to Evolve Art. In: EvoMUSART 2006, S. 633-641.



Human subjectivity have always posed a problem when it comes to judging designs. The line that divides what is interesting or not is blurred by the different interpretations as varied as the individuals themselves. Some approaches have made use of novelty in determining interestingness. However, computational measures of novelty such as the Euclidean distance are mere approximations to what the human brain finds interesting. In this paper, we explore the possibility of determining interestingness in a more direct method by using learning techniques such as Support Vector Machines to identify emotions from physiological signals, and then use genetic algorithms to evolve artworks that resulted in positive emotional signals.

Extended Abstract


booktitle={Applications of Evolutionary Computing},
series={Lecture Notes in Computer Science},
editor={Rothlauf, Franz and Branke, Jürgen and Cagnoni, Stefano and Costa, Ernesto and Cotta, Carlos and Drechsler, Rolf and Lutton, Evelyne and Machado, Penousal and Moore, JasonH. and Romero, Juan and Smith, GeorgeD. and Squillero, Giovanni and Takagi, Hideyuki},
title={Using Physiological Signals to Evolve Art},
url={ },
publisher={Springer Berlin Heidelberg},
author={Basa, Tristan and Go, ChristianAnthony and Yoo, Kil-Sang and Lee, Won-Hyung},

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Sonstige Links

Nima Bigdely Shamlo, Scott Makeig: Mind­Mirror: EEG­Guided Image Evolution. 2009