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(Die Seite wurde neu angelegt: „ == Reference == David Norton, Derrall Heath and Dan Ventura: Autonomously Creating Quality Images. In: Computational Creativity 2011 ICCC 2011, pp. 1…“)
 
Zeile 7: Zeile 7:
  
 
== Abstract ==
 
== Abstract ==
 +
Creativity is an important part of human intelligence, and it
 +
is difficult to quantify (or even qualify) creativity in an in-
 +
telligent system. Recently it has been suggested that quality,
 +
novelty, and typicality are essential properties of a creative
 +
system. We describe and demonstrate a computational sys-
 +
tem (called DARCI) that is designed to eventually produce
 +
images in a creative manner. In this paper, we focus on qual-
 +
ity and show, through experimentation and statistical analy-
 +
sis, that DARCI is beginning to be able to produce images
 +
with quality comparable to those produced by humans.
  
 
== Extended Abstract ==
 
== Extended Abstract ==
Zeile 13: Zeile 23:
  
 
== Used References ==
 
== Used References ==
 +
Colton, S.; Gow, J.; Torres, P.; and Cairns, P. 2010. Experi-
 +
ments in objet trouv ́e browsing. Proceedings of the Interna-
 +
tional Conference on Computational Creativity 238–247.
 +
 +
Colton, S. 2008. Creativity versus the perception of creativ-
 +
ity in computational systems. Creative Intelligent Systems:
 +
Papers from the AAAI Spring Symposium 14–20.
 +
 +
Datta, R.; Joshi, D.; Li, J.; and Wang, J. Z. 2006. Studying
 +
aesthetics in photographic images using a computational ap-
 +
proach. Lecture Notes in Computer Science 3953:288–301.
 +
 +
De Smedt, T.; De Bleser, F.; and Nijs, L. 2010. Nodebox 2.
 +
Proceedings of the 16th International Symposium on Elec-
 +
tronic Art (ISEA 2010).
 +
 +
Fellbaum, C., ed. 1998. WordNet: An Electronic Lexical
 +
Database. The MIT Press.
 +
 +
Gevers, T., and Smeulders, A. 2000. Combining color and
 +
shape invariant features for image retrieval. IEEE Transac-
 +
tions on Image Processing 9:102–119.
 +
 +
King, I. Distributed content-based visual informa-
 +
tion retrieval system on peer-to-pear(p2p) network.
 +
http://appsrv.cse.cuhk.edu.hk/~miplab/discovir/.
 +
 +
Li, C., and Chen, T. 2009. Aesthetic visual quality assess-
 +
ment of paintings. IEEE Journal of Selected Topics in Signal
 +
Processing 3:236–252.
 +
 +
Norton, D.; Heath, D.; and Ventura, D. 2010. Establishing
 +
appreciation in a creative system. Proceedings of the Inter-
 +
national Conference on Computational Creativity.
 +
 +
Ritchie, G. 2007. Some empirical criteria for attributing cre-
 +
ativity to a computer program. Minds and Machines 17:67–
 +
99.
 +
 +
Wang, W.-N., and He, Q. 2008. A survey on emotional
 +
semantic image retrieval. Proceedings of the International
 +
Conference on Image Processing.
 +
 +
Wang, W.-N.; Yu, Y.-L.; and Jiang, S.-M. 2006. Image re-
 +
trieval by emotional semantics: A study of emotional space
 +
and feature extraction. IEEE International Conference on
 +
Systems, Man, and Cybernetics 4:3534–3539.
  
  

Version vom 30. Januar 2015, 17:24 Uhr


Reference

David Norton, Derrall Heath and Dan Ventura: Autonomously Creating Quality Images. In: Computational Creativity 2011 ICCC 2011, pp. 10-15.

DOI

Abstract

Creativity is an important part of human intelligence, and it is difficult to quantify (or even qualify) creativity in an in- telligent system. Recently it has been suggested that quality, novelty, and typicality are essential properties of a creative system. We describe and demonstrate a computational sys- tem (called DARCI) that is designed to eventually produce images in a creative manner. In this paper, we focus on qual- ity and show, through experimentation and statistical analy- sis, that DARCI is beginning to be able to produce images with quality comparable to those produced by humans.

Extended Abstract

Bibtex

Used References

Colton, S.; Gow, J.; Torres, P.; and Cairns, P. 2010. Experi- ments in objet trouv ́e browsing. Proceedings of the Interna- tional Conference on Computational Creativity 238–247.

Colton, S. 2008. Creativity versus the perception of creativ- ity in computational systems. Creative Intelligent Systems: Papers from the AAAI Spring Symposium 14–20.

Datta, R.; Joshi, D.; Li, J.; and Wang, J. Z. 2006. Studying aesthetics in photographic images using a computational ap- proach. Lecture Notes in Computer Science 3953:288–301.

De Smedt, T.; De Bleser, F.; and Nijs, L. 2010. Nodebox 2. Proceedings of the 16th International Symposium on Elec- tronic Art (ISEA 2010).

Fellbaum, C., ed. 1998. WordNet: An Electronic Lexical Database. The MIT Press.

Gevers, T., and Smeulders, A. 2000. Combining color and shape invariant features for image retrieval. IEEE Transac- tions on Image Processing 9:102–119.

King, I. Distributed content-based visual informa- tion retrieval system on peer-to-pear(p2p) network. http://appsrv.cse.cuhk.edu.hk/~miplab/discovir/.

Li, C., and Chen, T. 2009. Aesthetic visual quality assess- ment of paintings. IEEE Journal of Selected Topics in Signal Processing 3:236–252.

Norton, D.; Heath, D.; and Ventura, D. 2010. Establishing appreciation in a creative system. Proceedings of the Inter- national Conference on Computational Creativity.

Ritchie, G. 2007. Some empirical criteria for attributing cre- ativity to a computer program. Minds and Machines 17:67– 99.

Wang, W.-N., and He, Q. 2008. A survey on emotional semantic image retrieval. Proceedings of the International Conference on Image Processing.

Wang, W.-N.; Yu, Y.-L.; and Jiang, S.-M. 2006. Image re- trieval by emotional semantics: A study of emotional space and feature extraction. IEEE International Conference on Systems, Man, and Cybernetics 4:3534–3539.


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