Using physiological signals to evolve art
- Authors
- Basa, T; Go, CA; Yoo, KS; Lee, WH
- Issue Date
- 2006
- Publisher
- SPRINGER-VERLAG BERLIN
- Citation
- APPLICATIONS OF EVOLUTIONARY COMPUTING, PROCEEDINGS, v.3907, pp 633 - 641
- Pages
- 9
- Journal Title
- APPLICATIONS OF EVOLUTIONARY COMPUTING, PROCEEDINGS
- Volume
- 3907
- Start Page
- 633
- End Page
- 641
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/52695
- DOI
- 10.1007/11732242_60
- ISSN
- 0302-9743
1611-3349
- Abstract
- 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.
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- Appears in
Collections - Graduate School of Advanced Imaging Sciences, Multimedia and Film > Department of Imaging Science and Arts > 1. Journal Articles
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