Authorship and Aesthetics Experiments: Comparison of Results between Human and Computational Systems

  • Luz Castro
  • Rebeca Perez
  • Antonino Santos
  • Adrian Carballal
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8601)


This paper presents the results of two experiments comparing the functioning of a computational system and a group of humans when performing tasks related to art and aesthetics. The first experiment consists of the identification of a painting, while the second one uses the Maitland Graves’s aesthetic appreciation test. The proposed system employs a series of metrics based on complexity estimators and low level features. These metrics feed a learning system using neural networks. The computational approach achieves similar results to those achieved by humans, thus suggesting that the system captures some of the artistic style and aesthetics features which are relevant to the experiments performed.


Fractal Dimension Computational System Aesthetics Experiment Aesthetic Judgement Aesthetic Preference 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Ekárt, A., Joó, A., Sharma, D., Chalakov, S.: Modelling the underlying principles of human aesthetic preference in evolutionary art. Journal of Mathematics and the Arts 6(2-3), 107–124 (2012)CrossRefGoogle Scholar
  2. 2.
    Eysenck, H.J., Castle, M.: Comparative study of artists and nonartists on the maitland graves design judgment test. Journal of Applied Psychology 55(4), 389–392 (1971)CrossRefGoogle Scholar
  3. 3.
    Götz, K., Götz, K.: The maitland graves design judgement test judged by 22. Perceptual and Motor Skills 39, 261–262 (1974)CrossRefGoogle Scholar
  4. 4.
    Greenfield, G., Machado, P.: Special issue: Mathematical models used in aesthetic evaluation. Journal of Mathematics and the Arts 6(2-3) (2012)Google Scholar
  5. 5.
    den Heijer, E.: Evolving glitch art. In: Machado, P., McDermott, J., Carballal, A. (eds.) EvoMUSART 2013. LNCS, vol. 7834, pp. 109–120. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  6. 6.
    Lewis, M.: Evolutionary visual art and design. In: Romero, J., Machado, P. (eds.) The Art of Artificial Evolution, pp. 3–37. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  7. 7.
    Machado, P., Cardoso, A.: Computing aesthetics. In: de Oliveira, F.M. (ed.) SBIA 1998. LNCS (LNAI), vol. 1515, pp. 219–228. Springer, Heidelberg (1998)CrossRefGoogle Scholar
  8. 8.
    Li, Y., Hu, C., Minku, L., Zuo, H.: Learning aesthetic judgements in evolutionary art systems. Genetic Programming and Evolvable Machines 14(3), 315–337 (2013), CrossRefGoogle Scholar
  9. 9.
    Machado, P., Romero, J., Manaris, B.: Experiments in computational aesthetics. In: Romero, J., Machado, P. (eds.) The Art of Artificial Evolution: A Handbook on Evolutionary Art and Music, pp. 381–415. Springer, Heidelberg (2007)Google Scholar
  10. 10.
    Romero, J., Machado, P., Carballal, A., Osorio, O.: Aesthetic classification and sorting based on image compression. In: Chio, C.D., et al. (eds.) EvoApplications 2011, Part II. LNCS, vol. 6625, pp. 394–403. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  11. 11.
    Romero, J., Machado, P., Carballal, A., Santos, A.: Using complexity estimates in aesthetic image classification. Journal of Mathematics and the Arts 6(2-3), 125–136 (2012)CrossRefMathSciNetGoogle Scholar
  12. 12.
    Romero, J., Machado, P., Santos, A., Cardoso, A.: On the development of critics in evolutionary computation artists. In: Raidl, G.R., et al. (eds.) EvoWorkshops 2003. LNCS, vol. 2611, pp. 559–569. Springer, Heidelberg (2003)Google Scholar
  13. 13.
    Taylor, R.P., Micolich, A.P., Jonas, D.: Fractal analysis of Pollock’s drip paintings. Nature 399, 422 (1999)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Luz Castro
    • 1
  • Rebeca Perez
    • 1
  • Antonino Santos
    • 1
  • Adrian Carballal
    • 1
  1. 1.Department of Information and Communication TechnologiesUniversity of A CoruñaA CoruñaSpain

Personalised recommendations