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== Reference ==
[[Tristan Basa | Basa, Tristan]]; [[Christian Anthony Go | Go, Christian Anthony]]; [[Kil-Sang Yoo | Yoo, Kil-Sang]]; [[Won-Hyung Lee | Lee, Won-Hyung]]: Using Physiological Signals to Evolve Art. In: [[Literatur_zur_Evolution%C3%A4ren_Kunst#EvoMUSART_2006_2 | EvoMUSART 2006]], S. 633-641.

== DOI ==
http://link.springer.com/10.1007/11732242_60

== 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.

== Extended Abstract ==

== Bibtex ==

== Used References ==
Saunders, R.: Curious Design Agents and Artificial Creativity. In: Proceedings of the 4th conference on Creativity & cognition, Loughborough, UK, pp. 80–87 (2002)

Collete, C., Vernet-Maury, E., Delhomme, G., Dittmar, A.: Autonomic Nervous System Response Patterns Specificity to Basic Emotions. Journal of the Autonomic Nervous System 62, 45–57 (1997)

Mori, M.: Wave UFO, http://www.publicartfund.org/pafweb/projects/03/mori_release_s03.html

Mitchell, T.: Machine Learning. McGraw-Hill Companies Inc., Singapore (1997)

Sims, K.: Artificial Evolution for Computer Graphics. Computer Graphics (Siggraph 1991 proceedings) 25(4), 319–328 (1991)

Christianini, N., Taylor, J.S.: An Introduction to Support Vector Machines and Other Kernel-Based Learning Methods. Cambridge University Press, UK (2000)

Ekman, P., Friesen, W.V.: The Facial Action Coding System. Consulting Psychologists Press, Paolo Alto (1978)

Levenson, R.W., Ekman, P., Friesen, W.V.: Voluntary facial action generates emotions specific autonomous nervous system activity. Psychophysiol 21 (1990)

Hubert, W., De Jong Meyer, R.: Psychophysiological response patterns to positive and negative film stimuli. Biol. Psychol., 73–93 (1990)

Hinrich, H., Machleidt, W.: Basic Emotions Reflected in EEG-coherences. International Journal of Phsychophysiology 13, 225–232 (1992)

Fridlung, A.J., Schwartz, G.E., Fowler, S.C.: Pattern Recognition of Self- Reported Emotional state from multiple-site facial EMG activity during affective imagery. Psyhophysiol. 21 (1984)

== Links ==
=== Full Text ===
[extern file]

[[intern file]]

=== Sonstige Links ===

[http://sccn.ucsd.edu/~nima/portfolio/downloads/mind_mirror_hci09.pdf Nima Bigdely Shamlo, Scott Makeig: MindMirror: EEGGuided Image Evolution. 2009]

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	== Bibtex ==		== Bibtex ==
		+	@incollection{
		+	year={2006},
		+	isbn={978-3-540-33237-4},
		+	booktitle={Applications of Evolutionary Computing},
		+	volume={3907},
		+	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},
		+	doi={10.1007/11732242_60},
		+	title={Using Physiological Signals to Evolve Art},
		+	url={http://dx.doi.org/10.1007/11732242_60 http://de.evo-art.org/index.php?title=Using_Physiological_Signals_to_Evolve_Art },
		+	publisher={Springer Berlin Heidelberg},
		+	author={Basa, Tristan and Go, ChristianAnthony and Yoo, Kil-Sang and Lee, Won-Hyung},
		+	pages={633-641},
		+	language={English}
		+	}

	== Used References ==		== Used References ==

Using Physiological Signals to Evolve Art - Versionsgeschichte

Gubachelier am 1. November 2015 um 21:21 Uhr

Gbachelier: Die Seite wurde neu angelegt: „ == Reference == Basa, Tristan; Go, Christian Anthony; Yoo, Kil-Sang; Won-Hyung Lee | Lee,…“