Computational Analysis Problem of Aesthetic Content in Fine-Art Paintings
https://doi.org/10.30727/0235-1188-2022-65-2-120-140
Abstract
The article discusses the possibilities of the formal analysis of the fine-art painting composition on the basis of the classical definitions of beauty and computational aesthetics’ approaches of the second half of the 20th century he authors define the problem and consider solutions for the formalization of aesthetic perception in the context of aesthetic text, i.e., as part of the fine arts composition – a formal sequence of signs simply ordered in accordance with the syntactic rules’ system. The methodology of the research is defined by the general semiotics, distinguishing semantics, syntax, and pragmatics of a sign, by the aesthetic analysis’ methods, ranging according to the author’s message aesthetics, receptive aesthetics, and text aesthetics, as well as by the computational analysis methods connected with neural network means of defining the images’ symmetry. The article reveals preconditions for the emergence and also the current state of computational aesthetics as an interdisciplinary branch of knowledge. Analyzing the problem from the perspective of philosophy, aesthetics, semiotics, and technology, the authors draw attention to the need to improve the computational aesthetics methods. Firstly, the existing methods do not always enable to describe the fine-art object adequately. Secondly, there exists the so-called reduction of aesthetic assertion transforming it into the assertion concerning the object’s external characteristics. As a result, the authors assume that the increasing complexity of the current mathematical models and the experts’ subjective assessment support will allow to reach a compromise solution that enables the development of computational aesthetics as a branch of knowledge. Enhancement and development of the mathematical models, taking into account the rules of semiotics and subjectivism of the human perception, is the relevant objective of computational analysis of the aesthetic fine-arts text. The results of the present research supports the classic statement regarding the underivability of semantic and pragmatic propositions from syntax. The research concludes that relevant objectives are to find a correlation between, one the one hand, the axes and points of symmetry, deriving from the neural simulation, and, on the other hand, aesthetic effect, emerging from the perception of fine-art paintings.
About the Authors
Olga A. ZhuravlevaRussian Federation
Olga A. Zhuravleva – postgraduate student, Russian and Foreign Literature and Public Relations Department; Lecturer, Pre-University Training Center, Samara National Research University.
Samara
Natalie B. Savkhalova
Russian Federation
Natalie B. Savkhalova – Colorist, “Center of Spiritual Culture” International Public Organization.
Samara
Andrei V. Komarov
Russian Federation
Andrei V. Komarov – Lecturer, English Language Department, Samara National Research University.
Samara
Denis A. Zherdev
Russian Federation
Denis A. Zherdev – Ph.D. in Technology, Senior Lecturer, Supercomputers and General Informatics Department, Samara National Research University.
Samara
Anna I. Demina
Russian Federation
Anna I. Demina – Teaching Specialist, Philosophy Department, Samara National Research University.
Samara
Eckart Michaelsen
Germany
Eckart Michaelsen – Dr. habil., Department of Object Recognition, Fraunhofer Institute of Optronics, System Technologies and Image Exploitation.
Ettlingen
Artem V. Nikonorov
Russian Federation
Artem V. Nikonorov – D.Sc. in Technology, Director of the Institute of Artificial Intelligence, Samara National Research University.
Samara
Alexander Yu. Nesterov
Russian Federation
Alexander Yu. Nesterov – D.Sc. in Philosophy, Associate Professor, Director of the Institute of Social Sciences and Humanities, Head of the Philosophy Department, Samara National Research University.
Samara
References
1. Alberti L.B. (1935) The Ten Books of Architecture: in 2 Vols (Vol. 1). Moscow: All-Union Architecture Academy Press (in Russian).
2. Bense M. (1968) Einfuhrung in die Informationsasthetik. In: Ronge H. (Ed.) Kunst und Kybernetik (pp. 28–41). Köln: DuMont (in German).
3. Birkhoff G.D. (1933) Aesthetic Measure. Cambridge: Harvard University Press.
4. Brachmann A. & Redies C. (2017) Computational and Experimental Approaches to Visual Aesthetics. Frontiers in Computational Neuroscience. Vol. 11, art. 102.
5. Cetinic E., Lipic T., & Grgic S. (2019) A Deep Learning Perspective on Beauty, Sentiment, and Remembrance of Art. IEEE Access. Vol. 7, pp. 73694–73710.
6. Cupchik G.C. (1986) A Decade after Berlyne: New Directions in Experimental Aesthetics. Poetics. Vol. 15, pp. 345–369.
7. Dhar S., Ordonez V., & Berg T.L. (2011) High Level Describable Attributes for Predicting Aesthetics and Interestingness. In: Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition (pp. 1657–1664). Los Alamitos, CA: IEEE Computer Society, 2018.
8. Ehsani K., Bagherinezhad H., Redmon J., Mottaghi R., & Farhadi A. (2018) Who Let The Dogs Out? Modeling Dog Behavior From Visual Data. In: Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 4051–4060). Los Alamitos, CA: IEEE Computer Society, 2018.
9. Fechner G.T. (1876) Vorschule der Aesthetik (Vol. 1). Leipzig: Breitkopf & Härtel (in German).
10. Hegel G.W.F. (1968) Aesthetics (Vols. 1−4; Vol. 1). Moscow: Iskusstvo (Russian translation).
11. Hegel G.W.F. (1973) Aesthetics (Vols. 1−4; Vol. 4). Moscow: Iskusstvo (Russian translation).
12. Hegel G.W.F. (2003) Vorlesungen über die Philosophie der Kunst (1823). Hamburg: Felix Meiner (in German).
13. Hoenig F. (2005) Defining Computational Aesthetics. In: Neumann L., Sbert M., Gooch B., Purgathofer W. Computational Aesthetics in Graphics, Visualization and Imaging. Retrieved from https://diglib.eg.org/xmlui/bitstream/handle/10.2312/COMPAESTH.COMPAESTH05.013-018/013-018.pdf?sequence=1
14. Ingarden R. (1962) Aesthetics Research. Moscow: Inostrannaya literatura (Russian translation).
15. Jakobson R. (1921) The Newest Russian Poetry. Sketch No. 1. Prague: Politika (in Russian).
16. Kant I. (1994) The Critique of Judgment. Moscow: Iskusstvo (Russian translation).
17. Kuznetsova A., Rom H., Alldrin N., Uijlings J., Krasin I., Pont-Tuset J., Kamali S., Popov S., Malloci M., Kolesnikov A., Duerig T., Ferrari V. (2020) The Open Images Dataset V4: Unified Image Classification, Object Detection, and Visual Relationship Detection at Scale. International Journal on Computer Vision. Vol. 128, no. 7, pp. 1956–1981.
18. Losev A.F. (2000) The History of Classical Aesthetics. Late Centuries. Moscow: AST Publishers (in Russian).
19. McWhinnie Н.J. (1968) A Review of Research on Aesthetic Measure. Acta Psychologica. Vol. 28, pp. 363—375 (Russian translation in: Artmetry. Methods of Exact Sciences and Semiotics. Moscow: Liberkom, 2009).
20. Michaelsen E. & Vujasinovic S. (2019) Estimating Efforts and Success of Symmetry-Seeing Machines by Use of Synthetic Data. Symmetry. Vol. 11, no. 2, pp. 1–16.
21. Nesterov A. & Demina A. (2019) An Artwork as a Technical Object.Mirgorod. Vol. 1, no. 13, pp. 48–74 (in Russian).
22. Shelling F. (1987) Works. Moscow: Mysl’ (in Russian).
23. Shannon C.E. Cybernetics and Information Theory. Moscow: Inostrannaya literatura (Russian translation).
24. Talebi H., Milanfar P. (2018) Nima: Neural Image Assessment. IEEE Transactions on Image Processing. Vol. 27, no. 8, pp. 3998–4011.
25. Volkov N.N. (1977) Composition in Painting. Moscow: Iskusstvo (in Russian).
26. Vygotsky L.S. (1986) The Psychology of Art. Moscow: Iskusstvo (in Russian).
27. Zhang R., Isola P., Efros A.A., Shechtman E., & Wang O. (2019) The Unreasonable Effectiveness of Deep Features as a Perceptual Metric. In: Proceedings of the 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 586–595). Los Alamitos, CA: IEEE
Review
For citations:
Zhuravleva O.A., Savkhalova N.B., Komarov A.V., Zherdev D.A., Demina A.I., Michaelsen E., Nikonorov A.V., Nesterov A.Yu. Computational Analysis Problem of Aesthetic Content in Fine-Art Paintings. Russian Journal of Philosophical Sciences. 2022;65(2):120-140. (In Russ.) https://doi.org/10.30727/0235-1188-2022-65-2-120-140