Abstract
The measure of complexity is a core concept in computational approaches to aesthetics. Shannon’s information theory provided an objective measure of complexity, which led to the emergence of various informational theories of aesthetics. However, entropy fails to consider the spatial characteristics of 2D patterns; these characteristics are fundamental in addressing the aesthetic problem. We propose two empirically evaluated alternative measures of complexity, considering the spatial characteristics of 2D patterns and experimental studies on human aesthetic perception in the visual domain. The first model, spatial complexity, is based on the probabilistic spatial distribution of pixels of a 2D pattern. The second model is based on algorithmic information theory (Kolmogorov complexity), which is extended to estimate the complexity of 2D patterns. The spatial complexity measure presents a performance advantage over information-theoretic models, specifically in discriminating symmetries and the orientation in 2D, enabling more accurate measurement of complexity in relation to aesthetic evaluations of 2D patterns. This paper examines whether the complexity measures for 2D patterns conform with aesthetic judgments. The experiment results show that none of the measures has a significant correlation with participants aesthetic rating/rankings of experimental stimuli.
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References
Andrienko, Yu. A., Brilliantov, N.V., Kurths, J.: Complexity of two-dimensional patterns. Eur. Phys. J. B 15(3), 539–546 (2000)
Arnheim, R.: Entropy and Art: An Essay on Disorder and Order. University of California Press, Oakland (1974)
Bates, J.E., Shepard, H.K.: Measuring complexity using information fluctuation. Phys. Lett. A 172(6), 416–425 (1993)
Cover, T.M., Thomas, J.A.: Elements of Information Theory (Wiley Series in Telecommunications and Signal Processing). Wiley-Interscience, New York (2006)
Jacobsen, T., Höfel, L.: Aesthetic judgments of novel graphic patterns: analyses of individual judgments. Percept. Mot. Skills 95(3), 755–766 (2002)
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 (LNAI), vol. 9273, pp. 201–212. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-23485-4_21
Javid, M.A.J., Blackwell, T., Zimmer, R., al-Rifaie, M.M.: Correlation between human aesthetic judgement and spatial complexity measure. In: Johnson, C., Ciesielski, V., Correia, J., Machado, P. (eds.) EvoMUSART 2016. LNCS, vol. 9596, pp. 79–91. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-31008-4_6
Kolmogorov, A.N.: Three approaches to the quantitative definition of information. Probl. Inf. Transm. 1(1), 1–7 (1965)
Li, M., Vitányi, P.: An Introduction to Kolmogorov Complexity and Its Applications. TCS, Springer, New York (2008). https://doi.org/10.1007/978-0-387-49820-1
Navratil, E., Zelinka, I., Senkerik, R.: Preliminary results of deterministic chaos control through complexity measures. In: 20th European Conference on Modelling and Simulation ECMS 2006: Modelling Methodologies and Simulation: Key Technologies in Academia and Industry. European Council for Modelling and Simulation (ECMS) (2006)
Shannon, C.: A mathematical theory of communication. Bell Syst. Tech. J. 27, 379–423, 623–656 (1948)
Wackerbauer, R., Witt, A., Atmanspacher, H., Kurths, J., Scheingraber, H.: A comparative classification of complexity measures. Chaos, Solitons Fractals 4(1), 133–173 (1994)
Ziv, J., Lempel, A.: Compression of individual sequences via variable-rate coding. IEEE Trans. Inf. Theory 24(5), 530–536 (1978)
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We are grateful to Thomas Jacobsen of Helmut Schmidt University for granting permission to use his experimental stimuli.
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Javaheri Javid, M.A. (2022). Aesthetic Evaluation of Experimental Stimuli Using Spatial Complexity and Kolmogorov Complexity. In: Martins, T., RodrĂguez-Fernández, N., Rebelo, S.M. (eds) Artificial Intelligence in Music, Sound, Art and Design. EvoMUSART 2022. Lecture Notes in Computer Science, vol 13221. Springer, Cham. https://doi.org/10.1007/978-3-031-03789-4_8
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