Correlation Between Human Aesthetic Judgement and Spatial Complexity Measure
Inhaltsverzeichnis
Referenz
Mohammad Ali Javaheri Javid, Tim Blackwell, Robert Zimmer, Mohammad Majid al-Rifaie: Correlation Between Human Aesthetic Judgement and Spatial Complexity Measure. In: EvoMUSART 2016, 79-91.
DOI
http://dx.doi.org/10.1007/978-3-319-16498-4_6
Abstract
The quantitative evaluation of order and complexity conforming with human intuitive perception has been at the core of computational notions of aesthetics. Informational theories of aesthetics have taken advantage of entropy in measuring order and complexity of stimuli in relation to their aesthetic value. However entropy fails to discriminate structurally different patterns in a 2D plane. This paper investigates a computational measure of complexity, which is then compared to a results from a previous experimental study on human aesthetic perception in the visual domain. The model is based on the information gain from specifying the spacial distribution of pixels and their uniformity and non-uniformity in an image. The results of the experiments demonstrate the presence of correlations between a spatial complexity measure and the way in which humans are believed to aesthetically appreciate asymmetry. However the experiments failed to provide a significant correlation between the measure and aesthetic judgements of symmetrical images.
Extended Abstract
Bibtex
@incollection{Javid2016, year={2016}, isbn={978-3-319-31007-7}, booktitle={Evolutionary and Biologically Inspired Music, Sound, Art and Design}, volume={9596}, series={Lecture Notes in Computer Science}, editor={Johnson, Colin and Ciesielski, Vic and Correia, João and Machado, Penousal}, doi={http://dx.doi.org/10.1007/978-3-319-16498-4_6}, title={Correlation Between Human Aesthetic Judgement and Spatial Complexity Measure}, url={http://link.springer.com/chapter/10.1007/978-3-319-31008-4_6 http://de.evo-art.org/index.php?title=Correlation_Between_Human_Aesthetic_Judgement_and_Spatial_Complexity_Measure }, publisher={Springer International Publishing}, keywords={Human aesthetic judgements, Spatial complexity, Information theory, Symmetry, Complexity}, author={Javid, Mohammad Ali Javaheri and Blackwell, Tim and Zimmer, Robert and al-Rifaie, Mohammad Majid}, pages={79-91}, language={English} }
Used References
1. Andrienko, Y.A., Brilliantov, N.V., Kurths, J.: Complexity of two-dimensional patterns. Eur. Phys. J. B 15(3), 539–546 (2000) http://dx.doi.org/10.1007/s100510051157
2. Arnheim, R.: Art and Visual Perception: A Psychology of the Creative Eye. Univ of California Press, Berkeley (1954)
3. Arnheim, R.: Towards a Psychology of Art/entropy and Art an Essay on Disorder and Order. The Regents of the University of California (1966)
4. Arnheim, R.: Visual Thinking. Univ of California Press, Berkeley (1969)
5. Bates, J.E., Shepard, H.K.: Measuring complexity using information fluctuation. Phys. Lett. A 172(6), 416–425 (1993) http://dx.doi.org/10.1016/0375-9601(93)90232-O
6. Bense, M., Nee, G.: Computer grafik. In: Bense, M., Walther, E. (eds.) Edition Rot, vol. 19. Walther, Stuttgart (1965)
7. Bense, M.: Aestetica: Programmierung des Schönen, allgemeine Texttheorie und Textästhetik [Aesthetica : Programming of beauty, general text theory and aesthetics]. Agis-Verlag (1960)
8. Bense, M.: Kleine abstrakte ästhetik [small abstract aesthetics]. In: Walther, E. (ed.) Edition Rot, vol. 38 (1969)
9. Birkhoff, G.: Aesthetic Measure. Harvard University Press, Cambridge (1933) http://dx.doi.org/10.4159/harvard.9780674734470
10. Victor Ciesielski, Perry Barile, Karen Trist: Finding Image Features Associated with High Aesthetic Value by Machine Learning. In: EvoMUSART 2013, 47-58. DOI: http://link.springer.com/10.1007/978-3-642-36955-1_5 http://www.cs.rmit.edu.au/~vc/papers/evomusart13.pdf
11. Cover, T.M., Thomas, J.A.: Elements of Information Theory. Wiley Series in Telecommunications and Signal Processing. Wiley-Interscience, New York (2006)
12. Dawkins, R.: The Blind Watchmaker. W. W. Norton, New York (1986)
13. Heijer, Eelco den; Eiben, A. E.: Comparing Aesthetic Measures for Evolutionary Art. In: EvoMUSART 2010, 311-320. DOI: http://link.springer.com/10.1007/978-3-642-12242-2_32 http://www.few.vu.nl/~eelco/publications/E-den-Heijer-and-AE-Eiben-Comparing-aesthetic-Measures-for-Evolutionary-Art-2010.pdf
14. Eysenck, H.J.: An experimental study of aesthetic preference for polygonal figures. J. Gen. Psychol. 79(1), 3–17 (1968) http://dx.doi.org/10.1080/00221309.1968.9710447
15. Eysenck, H.J.: The empirical determination of an aesthetic formula. Psychol. Rev. 48(1), 83 (1941) http://dx.doi.org/10.1037/h0062483
16. Eysenck, H.J.: The experimental study of the ‘good gestalt’ –a new approach. Psychol. Rev. 49(4), 344 (1942) http://dx.doi.org/10.1037/h0057013
17. Franke, H.W.: A cybernetic approach to aesthetics. Leonardo 10(3), 203–206 (1977) http://dx.doi.org/10.2307/1573423
18. Philip Galanter: Computational Aesthetic Evaluation: Past and Future. In: McCormack & d’Inverno: Computers and Creativity, Springer, Berlin, 2012, 255-293 DOI: http://link.springer.com/chapter/10.1007/978-3-642-31727-9_10 http://philipgalanter.com/downloads/galanter_computational_aesthetic_evaluation_springer.pdf
19. Eelco Heijer: Autonomous Evolutionary Art. PhD Thesis, VRIJE UNIVERSITEIT, 2013, ISBN 9789461919519. http://eelcodenheijer.nl/phd_thesis_Eelco_den_Heijer.pdf
20. Jacobsen, T.: Beauty and the brain: culture, history and individual differences in aesthetic appreciation. J. Anat. 216(2), 184–191 (2010) http://dx.doi.org/10.1111/j.1469-7580.2009.01164.x
21. Jacobsen, T., Hofel, L.: Aesthetic judgments of novel graphic patterns: analyses of individual judgments. Percept. Mot. Skills 95(3), 755–766 (2002) http://dx.doi.org/10.2466/pms.2002.95.3.755 (DOI lead to nothing??? Reference found with abstract: http://www.ncbi.nlm.nih.gov/pubmed/12509172)
22. Javaheri Javid, M.A., Blackwell, T., Zimmer, R., Al-Rifaie, M.M.: Spatial complexity measure for characterising cellular automata generated 2D patterns. In: Pereira, F., Machado, P., Costa, E., Cardoso, A. (eds.) EPIA 2015. LNCS, vol. 9273, pp. 201–212. Springer, Heidelberg (2015) http://dx.doi.org/10.1007/978-3-319-23485-4_21
23. Javid, M.A.J., al-Rifaie, M.M., Zimmer, R.: An informational model for cellular automata aesthetic measure. In: AISB Symposium on Computational Creativity. University of Kent, Canterbury, UK (2015) https://www.cs.kent.ac.uk/events/2015/AISB2015/proceedings/computationalCreativity/AISB-CC2015.pdf
24. Latham, W.H., Todd, S.: Computer sculpture. IBM Syst. J. 28(4), 682–688 (1989) http://dx.doi.org/10.1147/sj.284.0682
25. Li, M., Vitányi, P.: An Introduction To Kolmogorov Complexity and its Applications. 3nd edn. Springer, New York (2008). http://www.springer.com/mathematics/applications/book/978-0-387-33998-6 http://dx.doi.org/10.1007/978-1-4757-2606-0
26. Penousal Machado, Amílcar Cardoso: Computing aesthetics. In: de Oliveira, F.M. (ed.) SBIA 1998. LNCS (LNAI), vol. 1515, pp. 219–228. Springer, Heidelberg (1998) DOI: http://dx.doi.org/10.1007/10692710_23 http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.37.6406 http://fmachado.dei.uc.pt/wp-content/papercite-data/pdf/mc98.pdf
27. Machado, Penousal; Romero, Juan; Manaris, Bill: Experiments in Computational Aesthetics. In: Juan Romero; Penousal Machado: The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music. Springer, Berlin, 2007, 381-415. DOI: http://link.springer.com/10.1007/978-3-540-72877-1_18 http://fmachado.dei.uc.pt/wp-content/papercite-data/pdf/mrm07a.pdf
28. Jon McCormack: Open Problems in Evolutionary Music and Art. In: EvoMUSART 2005, 428-436. DOI: http://link.springer.com/10.1007/978-3-540-32003-6_43 http://www.csse.monash.edu.au/~jonmc/research/Papers/OpenProblemsSV.pdf
29. McCormack, Jon: Facing the Future: Evolutionary Possibilities for Human-Machine Creativity. In: Juan Romero; Penousal Machado: The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music. Springer, Berlin, 2007, 417-451. DOI: http://dx.doi.org/10.1007/978-3-540-72877-1_19 http://www.csse.monash.edu.au/~jonmc/research/Papers/FacingTheFutureEXTRACT.pdf
30. Moles, A.: Information Theory and Esthetic Perception. Illinois Press, Urbana (1968). Trans. JE Cohen. U
31. Nake, F.: Information aesthetics: an heroic experiment. J. Math. Arts 6(2–3), 65–75 (2012) http://dx.doi.org/10.1080/17513472.2012.679458
32. Noll, A.M.: The digital computer as a creative medium. IEEE Spectr. 4(10), 89–95 (1967) http://dx.doi.org/10.1109/MSPEC.1967.5217127
33. Rigau, J., Feixas, M., Sbert, M.: Informational Aesthetics Measures. IEEE Computer Graphics and Applications, 24–34 (2008). DOI: http://dx.doi.org/10.1109/MCG.2008.34
34. Jaume Rigau, Miquel Feixas, Mateu Sbert: Conceptualizing Birkhoff's Aesthetic Measure Using Shannon Entropy and Kolmogorov Complexity. In: Douglas W. Cunningham, Gary W. Meyer, László Neumann, Alan Dunning, Raquel Paricio (Eds.):Eurographics Workshop on Computational Aesthetics 2007. 105-112 DOI: http://dx.doi.org/10.2312/COMPAESTH/COMPAESTH07/105-112 http://ima.udg.edu/~rigau/Publications/Rigau07B.pdf
35. Shannon, C.: A mathematical theory of communication. Bell Syst. Tech. J. 27, 379–423, 623–656 (1948)
36. Sims, K.: Artificial evolution for computer graphics. Technical Report, TR-185, Thinking Machines Corporation (1991)
Karl Sims: Artificial evolution for computer graphics. In: SIGGRAPH 1991 Proceedings, vol. 25, pp. 319–328. ACM, New York (1991), http://dx.doi.org/10.1145/122718.122752 http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.161.2547 http://www.karlsims.com/papers/siggraph91.html http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.161.2547&rep=rep1&type=pdf
37. Staudek, T. (2002). Exact Aesthetics. Object and Scene to Message. PhD thesis. Faculty of Informatics, Masaryk University of Brno.
38. Wackerbauer, R., Witt, A., Atmanspacher, H., Kurths, J., Scheingraber, H.: A comparative classification of complexity measures. Chaos, Solitons & Fractals 4(1), 133–173 (1994) http://dx.doi.org/10.1016/0960-0779(94)90023-X
39. Wilson, D.J.: An experimental investigation of Birkhoff’s aesthetic measure. J. Abnorm. Soc. Psychol. 34(3), 390 (1939) http://dx.doi.org/10.1037/h0059439
40. Zurek, W.H.: Algorithmic randomness and physical entropy. Phys. Rev. A 40(8), 4731 (1989) http://dx.doi.org/10.1103/PhysRevA.40.4731
Links
Full Text