Investigating aesthetic measures for unsupervised evolutionary art

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Reference

Eelco den Heijer and A. E. Eiben: Investigating aesthetic measures for unsupervised evolutionary art. Swarm and Evolutionary Computation 16, 2014, 52--68.

DOI

http://dx.doi.org/10.1016/j.swevo.2014.01.002

Abstract

We present an extensive study into aesthetic measures in unsupervised evolutionary art (EvoArt). In contrast to several mainstream EvoArt approaches we evolve images without human interaction, using one or more aesthetic measures as fitness functions. We perform a series of systematic experiments, comparing 7 different aesthetic measures through subjective criteria (‘style’) as well as by quantitative measures reflecting properties of the evolved images. Next, we investigate the correlation between aesthetic scores by aesthetic measures and calculate how aesthetic measures judge each others images. Furthermore, we run experiments in which two aesthetic measures are acting simultaneously using a Multi-Objective Evolutionary Algorithm. Hereby we gain insights in the joint effects on the resulting images and the compatibility of different aesthetic measures.

Extended Abstract

Bibtex

Used References

[1] R. Dawkins, The Blind Watchmaker, Penguin Books, 1986.

[2] H. Takagi, Interactive evolutionary computation: Fusion of the capacities of ec optimization and human evaluation, Proceedings of the IEEE 89 (9) (2001) 1275–1296.

[3] K. Sims, Artificial evolution for computer graphics, SIGGRAPH ’91: Pro- ceedings of the 18th annual conference on Computer graphics and interac- tive techniques 25 (4) (1991) 319–328.

[4] S. Rooke, Eons of genetically evolved algorithmic images, in: Bentley and Corne [7], pp. 339–365.

[5] P. Machado, A. Cardoso, All the truth about NEvAr, Applied Intelligence 16 (2) (2002) 101–118.

[6] J. Romero, P. Machado (Eds.), The Art of Artificial Evolution: A Hand- book on Evolutionary Art and Music, Natural Computing Series, Springer Berlin Heidelberg, 2007.

[7] P. J. Bentley, D. W. Corne (Eds.), Creative Evolutionary Systems, Morgan Kaufmann, San Mateo, California, 2001.

[8] S. Baluja, D. Pomerleau, T. Jochem, Towards automated artificial evolution for computer-generated images, Connection Science 6 (1994) 325–354.

[9] P. Machado, A. Cardoso, Computing aesthetics, in: Proceedings of the Brazilian Symposium on Artificial Intelligence, SBIA-98, Springer-Verlag, 1998, pp. 219–229.

[10] B. J. Ross, W. Ralph, H. Zong, Evolutionary image synthesis using a model of aesthetics, in: IEEE Congress on Evolutionary Computation (CEC) 2006, 2006, pp. 1087–1094.

[11] G. R. Greenfield, On the origins of the term ”computational aesthetics”, in: Neumann et al [43], pp. 9–12.

[12] F. Hoenig, Defining computational aesthetics, in: Neumann et al [43], pp. 13–18.

[13] P. Galanter, Computational aesthetic evaluation: Past and future, in: J. McCormack, M. d’Inverno (Eds.), Computers and Creativity, Springer, Berlin Heidelberg, 2012, Ch. 10, pp. 255–293.

[14] C. G. Johnson, Fitness in evolutionary art and music: What has been used and what could be used?, in: P. Machado, J. Romero, A. Carballal (Eds.), Evolutionary and Biologically Inspired Music, Sound, Art and Design, Vol. 7247 of Lecture Notes in Computer Science, Springer Berlin Heidelberg, 2012, pp. 129–140.

31[15] E. den Heijer, A. E. Eiben, Using aesthetic measures to evolve art, in: IEEE Congress on Evolutionary Computation, IEEE Press, 2010, pp. 311–320.

[16] E. den Heijer, A. E. Eiben, Comparing aesthetic measures for evolution- ary art, in: Applications of Evolutionary Computation, LNCS vol. 6025, Springer, 2010, pp. 311–320.

[17] E. den Heijer, A. E. Eiben, Evolving art using multiple aesthetic measures, in: EvoApplications, LNCS 6625, 2011, 2011, pp. 234–243.

[18] J.-M. Jolion, Images and benford’s law, Journal of Mathematical Imaging and Vision 14 (1) (2001) 73–81.

[19] B. Spehar, C. W. G. Cli↵ord, B. R. Newell, R. P. Taylor, Universal aesthetic of fractals., Computers & Graphics 27 (5) (2003) 813–820.

[20] K. Matkovic, L. Neumann, A. Neumann, T. Psik, W. Purgathofer, Global contrast factor-a new approach to image contrast, in: Neumann et al [43], pp. 159–168.

[21] J. Rigau, M. Feixas, M. Sbert, Informational aesthetics measures, IEEE Computer Graphics and Applications 28 (2) (2008) 24–34.

[22] E. den Heijer, Evolving glitch art, in: P. Machado, J. McDermott, A. Car- ballal (Eds.), EvoMUSART, Vol. 7834 of Lecture Notes in Computer Sci- ence, Springer, 2013, pp. 109–120.

[23] E. del Acebo, M. Sbert, Benford’s law for natural and synthetic images, in: Neumann et al [43], pp. 169–176.

[24] R. Saunders, J. S. Gero, The digital clockwork muse: A computational model of aesthetic evolution, in: The AISB’01 Symposium on AI and Cre- ativity in Arts and Science, SSAISB, 2001, pp. 12–21.

[25] S. Wannarumon, E. l. j. Bohez, K. Annanon, Aesthetic evolutionary algo- rithm for fractal-based user-centered jewelry design, Artif. Intell. Eng. Des. Anal. Manuf. 22 (1) (2008) 19–39.

[26] P. Machado, H. Nunes, J. Romero, Graph-based evolution of visual languages, in: Applications of Evolutionary Computation, LNCS 6025, Springer, 2010, pp. 271–280.

[27] D. Atkins, R. Klapaukh, W. Browne, M. Zhang, Evolution of aesthetically pleasing images without human-in-the-loop, in: Evolutionary Computation (CEC), 2010 IEEE Congress on, 2010, pp. 1–8.

[28] J. R. Koza, Genetic programming: on the programming of computers by means of natural selection, The MIT Press, Cambridge, MA, 1992.

[29] G. R. Greenfield, Mathematical building blocks for evolving expressions, in: R. Sarhangi (Ed.), 2000 Bridges Conference Proceedings, Central Plain Book Manufacturing, 2000, pp. 61–70.

[30] C. A. Pickover, Computers, Pattern, Chaos and Beauty: Graphics from an Unseen World, St. Martins Press, New York, 1990.

[31] G. R. Greenfield, Evolving aesthetic images using multiobjective optimiza- tion, in: Proceedings of the 2003 Congress on Evolutionary Computation CEC 2003, IEEE Press, 2003, pp. 1903–1909.

[32] S. Zeki, Inner Vision: An Exploration of Art and the Brain, Oxford Uni- versity Press, USA, 2000.

[33] B. J. Ross, H. Zhu, Procedural texture evolution using multi-objective op- timization, New Gen. Comput. 22 (3) (2004) 271–293.

[34] K. Deb, A. Pratap, S. Agarwal, T. Meyarivan, A fast elitist multi-objective genetic algorithm: NSGA-II, IEEE Transactions on Evolutionary Compu- tation 6 (2002) 182–197.

[35] S. Bergen, B. J. Ross, Evolutionary art using summed multi-objective ranks, in: R. R. et al (Ed.), Genetic Programming Theory and Practice VIII, Vol. 8 of Genetic and Evolutionary Computation, Springer, Ann Ar- bor, USA, 2010, Ch. 14, pp. 227–244.

[36] L. Neumann, A. Nemcsics, A. Neumann, Computational color harmony based on coloroid system, in: Neumann et al [43], pp. 231–240.

[37] J. Nesetril, Aesthetics for computers, or how to measure harmony, in: M. Emmer (Ed.), The Visual Mind II, MIT Press, 2005, pp. 35–59.

[38] P. Moon, D. Eberle Spencer, Aesthetic measure applied to color harmony, Journal of the Optical Society of America (1917-1983) 34 (1944) 234–242.

[39] F. Birren, Principles of color: a review of past traditions and modern the- ories of color harmony, Schi↵er Publishing, 1987.

[40] E. den Heijer, Evolving symmetric and balanced art, Studies in Computa- tional Intelligence.

[41] S.-Z. Zhao, P. N. Suganthan, Q. Zhang, Decomposition-based multiobjec- tive evolutionary algorithm with an ensemble of neighborhood sizes., IEEE Trans. Evolutionary Computation 16 (3) (2012) 442–446.

[42] A. Zhou, B.-Y. Qu, H. Li, S.-Z. Zhao, P. N. Suganthan, Q. Zhang, Multi- objective evolutionary algorithms: A survey of the state of the art., Swarm and Evolutionary Computation 1 (1) (2011) 32–49.

[43] L. Neumann et al (Ed.), Computational Aesthetics 2005, Eurographics As- sociation, 2005.


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http://www.researchgate.net/profile/Eelco_Den_Heijer/publication/260014748_Investigating_Aesthetic_Measures_for_Unsupervised_Evolutionary_Art/links/00b7d52fa1e41da05e000000?ev=pub_ext_doc_dl&origin=publication_detail&inViewer=true

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