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ІСТОРІЯ ТА ТЕОРІЯ МИСТЕЦТВА
DOI: 10.31866/2410-1176.42.2020.207634
UDC 75.02:004
Tetiana Sovhyra
PhD in Art Studies, Senior Lecturer,
ORCID: 0000-0002-7023-5361,
e-mail: STIsovgyra@gmail.com,
Kyiv National University of Culture and Arts,
36, Ye. Konovaltsia St., Kyiv, Ukraine, 01133
The purpose of the article is to analyse the modern visual digitally created artworks, to nd out the particularity of
their application and to identify the relations between traditional and innovative methods in modern painting; to consider
the method of applying paint and the functional component of 3D printing in the process of paintings “production”. The
research methodology is a complex of several methods: analytical
–
to examine the historical literature and literature
on the art studies, theoretical and conceptual method
–
to characterise the terminological system of the research, and
also comparative and typological
–
to compare traditional technologies of painting with innovative and digital ones.
The scientic novelty of the research is to identify the features of the introduction of digital technologies in visual art.
Conclusions. It was revealed that with the help of technology of “articial intelligence”, it becomes possible to recreate
the lost fragments of images. It was demonstrated that due to the technology of three-dimensional printing, it is possible
not only to make copies, but also to create unique artistic compositions. It was shown that thanks to the algorithmic
analysis and mathematical modelling, it is possible to establish a certain ratio of sign systems of musical and pictorial
works and, based on the identied results of algorithmic calculation, to establish a certain ratio of expressive means of art
in digital (mathematical) equivalent. Thus, due to “articial intelligence”, it is possible to synthesize different types of art
in one work and use the methods of various branches of knowledge. Having analysed the facts of introduction of digital
technologies, algorithmic analysis of paintings and 3D printing technology, we can state the fact that algorithmic art is
only at the rst stage of its development and has great prospects for the future.
Keywords: digital technologies; painting; technique; algorithmic art; generative neural network
Introduction
Technological features of artwork creation have always been a relevant topic for the scientic research,
taking into account the introduction of technical innovations in all spheres of human life, which is conrmed
by a signicant number of related publications.
Foreign scientic research by A. Ruesseler (2006), P. Daum (Daum et al., 2006), R. Askott (2004),
F. Stedman, as well as domestic research by V. Zatserkovnyi and N. Karevina (2014), Ya. Prudenko (2014),
Yu. Miliutina (2011) study the issue of innovation in art. As L. Molchanova (2010) rightly points out: “the
emergence of innovations in the visual art is connected with the cultural changes in society, with the devel-
opment of industrial civilization, which, unlike traditional civilizations, focuses on continuous scientic and
technical progress, accelerates and directly affects the artist” (p. 37). The author of this article agrees with this
view and at the same time emphasizes that these interactions can be applied to all types of art.
Methods of painting techniques, the use of various colours, mixtures and laws of colour are studied in
the works of the artist Zh. Viber (1961), graphic artist L. Feinberg and art critic Yu. Grenberg (1989). The
historical aspect of painting is considered in the scientic research of E. Berger (1961).
In recent years, signicant historical, cultural and theoretical works have been published, where much
attention is paid to the introduction of digital technologies in various elds of art, including painting. In par-
ticular, D. Shavlygin and A. Obmorokova (2015) and V. Shcheglov (2017) explore the relationship between
digital technologies and art. V. Shcheglov points out to a number of repeated sequences in the context of
artistic content, which the author calls algorithms, and thus the painting – an algorithmic system. The signif-
icance of the introduction of digital technologies in the socio-cultural sphere is contemplated in the works of
M. Lovejoy (2004), F. Popper (2007) and D. Galkin (2013). However, among the signicant number of scien-
tic studies that address the issues of painting, there is a lack of work devoted to the study of the introduction
of modern digital technologies in the art of painting.
DIGITAL TECHNOLOGIES
IN MODERN VISUAL ART
© Tetiana Sovhyra, 2020
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The scientic novelty of the research is that this article analyses the principles of creating of a modern
visual artwork with the help of digital technologies and also explores the uniqueness of such works for the
rst time.
Purpose of the article
The purpose of the article is to analyse modern visual digitally created artworks, to nd out the particu-
larity of their application and to identify the relations between traditional and innovative methods in modern
painting; to consider the method of applying paint and the functional component of 3D printing in the process
of paintings “production”.
Main research material
Painting technologies have been changed with time, trends, and the development of the technical compo-
nent of ne art. It is known that the rst cave paintings were carved with stones and show images of the animal
world typical for that time (buffaloes, mammoths, rhinos, lions, etc.). The oldest image is about 40,000 years
old. At that time, the tools for creating the rst drawings were stones and natural, organic pigments. An ex-
ample is the cave paintings in the Rock Shelters of Bhimbetka, India (about 9,000 years old), created with red
ochre, red and black pigments (Pic. 1).
As you know, the technology is a method of using tools (stones, pigment, brush, paint). In the historical
cross-section of art, there is a certain ratio of its technical and technological component: the more complex
is the technique (tools), the easier is the technology of its application for a person. And vice versa: using
of a simple tool requires more complex work. Example: it took primitive man a long time to carve an im-
age on a cave wall. However, now a person with a set of modern tools spends less time to create the same
drawing.
As the historical development of paintings shows, with the advent of new materials and tools (brushes,
paints, gouaches or tempera) the image application technology has been changing. Therefore, now there are
many painting techniques -tempera, gouache, pastel, ink, fresco, grattage, grisaille, glue paints, watercol-
ours, acrylics, wax painting, which names are often identical to expendable materials. Today, in the process
of painting, apart from tools and raw materials, computer equipment is used, which radically changes the
technology of making works of visual art.
Articial intelligence is a technology that can be used to perform a number of manipulations in a certain
sequence programmed by a person. It is well known that copies of works by famous artists are created using
Picture 1. Cave art. The Bhimbetka rock shelters, India, the Stone Age
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articial intelligence. The famous event was the New York auction, 2018, where a copy of Rembrandt’s “Ed-
mond de Belamy, from La Famille de Belamy” was sold for $ 432,500 (Cohn, 2018).
“New Rembrandt” (original name “The Next Rembrandt”) - a portrait-painting that reproduces the crea-
tive style of Rembrandt with exceptional accuracy, but is not a copy of the image of the famous paintings of the
master (Pic. 2). The work became possible due to the use of “articial intelligence” technologies. Experts from
Microsoft, Delft University of Technology, the Mauritshuis Royal Picture Gallery and the Rembrandt House
Museum in Amsterdam, using Microsoft Azure computing resources and a number of specialized algorithms,
conducted a three-dimensional scan of 346 paintings of the artist and found out not only genre and stylistic
specics, but also the artist’s typical techniques and techniques for working with oil paints. A painting, which
was created as a result of an 18-month-long study of the artist’s works with the help of 3D printing, showed
that articial intelligence technologies could produce a unique art product that imitated the work of a famous
artist, but have its own content.
The example of the “New Rembrandt” shows that the mathematical analysis of the artists’ creation makes
it possible to detect certain algorithms of the artist’s (author’s) work, analyse the main components of an ar-
tistic work, and transform the sign system of art into a system of different organization – a numerical one. So,
the colour, shape, and location of the objects depicted on the canvas (a composition) are all converted into
numerical formulas and combinations. The graphic image is transformed into a digital, algorithmic one. A cer-
tain system of numbers is built, which makes it possible to use the obtained numerical combinations to group
works (of the same artist, epoch, art direction) into single systems-collections, analyse and identify similar
algorithmic chains and create new art products based on these algorithms.
The denition of “products of art” (not works of art) is used intentionally due to the fact that a work as
a result of the creativity can only be created by a person. And “articial intelligence” technologies can produce
objects that can only claim a right to be considered artistic.
Now, with the help of “articial intelligence” technology, you can recreate lost images and even damaged
fragments of famous paintings.
The painting of the famous Spanish artist Pablo Picasso “The Old Guitarist” was created on the canvas of
another, previously painted picture “Sitting Woman” (Pic. 3). This fact became known thanks to the radiog-
raphy during the restoration of the painting. However, it was not possible to see the distinct image, it was too
difcult to reproduce it for everyone to see. Using a neural network of articial intelligence, which due to the
algorithmic analysis can distinguish the style of one artist from another (as with the work of P. Picasso - to dif-
ferentiate one period from another), researchers from the University College of London have created an exact
copy of the hidden picture of Picasso. The neural network is based on the technique of “neural style transfer”
by Leon Gatys (from the University of Tübingen, Germany, 2015), according to which the machine scanning
Picture 2. “The Next Rembrandt”, 2016.
Creators: ING Bank, J. Walter Thompson Amsterdam, Microsoft, TU Delft, Mauritshuis, Museum Het Rembrandthis
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technique can determine the style of a picture and use it in the creation of a completely different image. Dur-
ing the study, researchers Anthony Bourached and George Cann analysed the style of another masterpiece
of Picasso’s Blue Period “La Vie” (1903) and using a 3D printer reproduced an image of a woman taking into
account the stylistic features of the artist.
If modern art products are created using algorithmic analysis, then the production process can also be
considered as an algorithmic art.
Algorithmic analysis is possible in various elds of art –
graphics, painting, architecture, music, and so on.
Researchers have been studying the synthesis of differ-
ent types of art for a long time – painting and drawing, mu-
sic and choreography, sculpture and architecture, theatre and
cinema. Artists inspired by music draw the pictures, and vice
versa, under the inuence of visual art, musical, architectur-
al and screen works are created. These forms of interaction
between different types of art have been known for a long
time. However, today, it is possible to perform a comparative
analysis of several artistic works based on algorithmic calcu-
lation and establish a certain ratio of the expressive means of
art in the digital (mathematical) equivalent.
Signicant within the framework of the research is the
work “Kandinsky” of Microsoft company created due to the
algorithmic analysis of Kandinsky’s paintings, the musical
work of Richard Wagner (the opera “Lohengrin”, 1916), the
atonal compositions by Arnold Schoenberg, as well as works
of modern music.
Due to the generative neural network, the algorithmic
construction of the works of the artist, music compositions by R. Wagner, A. Schoenberg have been ana-
lysed, the ratio of the image and sound has been revealed. For example, each colour shade corresponds to
a certain sound, and the combination of dots and strokes corresponds to a certain leitmotif.
Changing the melodic pattern, the image is changing accordingly. Random combinations added to the
sound sequence start making changes to the visual content. There is an internal creative improvisation in
the creation of an image. Works of modern musical directions are also subjected to comparative algorithmic
analysis and accompanied by pictorial visualization in accordance with the algorithms for creating a painting
by the artist V. Kandinsky. Thus, articial intelligence shows us how an artist would paint a picture today if
he listened to modern music, instead of being inspired by the work of famous expressionists.
“Generative adversarial networks are constructed in the following way – two networks contest with
each other – one, based on its stock of samples, creates new images, and the second evaluates them. This
method is used to solve a variety of issues, but it is the example of art that appeared to be the most obvious.
The picture allows us not only to understand better how modern methods of articial intelligence work, but
also to get closer to understanding of the creative process itself,” said Vladislav Shershulsky Director for
Prospective Technologies, Microsoft Russia.
The example of this project shows how due to algorithmic analysis and modelling, a certain ratio of sign
systems of musical and pictorial works is determined. A person cannot predict how the images will change
and, in the end, what the nal result of the work will be.
So, we can state the fact that articial intelligence technology creates art products that are unique in their
kind. The production of digitally created art products is an algorithmic art. Painting created by “articial
intelligence” becomes algorithmic painting.
At the same time, we do not deny the uniqueness of human activity and artistic creativity. Moreover,
we insist on the need to develop a symbiosis between man and digital technologies in art: to combine the
capabilities of “articial intelligence”, aesthetic sensitivity and creative activity of a man.
Conclusions
It was revealed that with the help of digital technology, which is now called “articial intelligence”, it
becomes possible to recreate the lost fragments of images of paintings. On the example of the painting by
Picture 3. “Sitting Woman” by Pablo Picasso
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P. Picasso “Sitting Woman” it is shown that now only with the help of “articial intelligence” it is possible to
reproduce hidden fragments of the image.
It was demonstrated that due to the technology of three-dimensional printing, it is possible not only to
make copies, but also to create unique artistic compositions.
It was shown that thanks to algorithmic analysis and mathematical modelling, it is possible to establish
a certain ratio of sign systems of musical and pictorial works and, based on the identied results of algorithmic
calculation, to establish a certain ratio of expressive means of art in digital (mathematical) equivalent. Thus,
due to “articial intelligence”, it is possible to synthesize different types of art in one work and use the methods
of various branches of knowledge.
Having analysed the facts of introduction of digital technologies, algorithmic analysis of paintings and 3D
printing technology, we can state the fact that algorithmic art is only at the rst stage of its development and
has great prospects for the future.
References
Askott, R. (2004). Interaktivnoe iskusstvo: na poroge postbiologicheskoi kultury [Interactive Art: On the Threshold
of Post-Biological Culture]. In D. Bulatov (Ed.), Biomediale: Sovremennoe obshchestvo i genomnaia kultura
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questions of the denition of the concepts of "innovation" and "novelty"]. The University Scientic Notes, 4,
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Molchanova, L. A. (2010). Poniatiia "innovatciia" i "traditciia" v iskusstve [The concepts of "innovation" and "tradition"
in art]. In Snitkovskie chteniia [Snitkov readings] (pp. 37-43). Altaiskii dom pechati [in Russian].
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Prudenko, Ya. (2014, December 17). Klasychni vydy mystetstva v epokhu novitnikh tekhnolohii. Zhyvopys [Classic art
in the age of the latest technology. Painting]. Art Ukraine. http://artukraine.com.ua/a/klasichni-vidi-mistectva-v-
epokhu-novitnikh-tekhnologiy-zhivopis/#.Xo4L_kAzZdg [in Ukrainian].
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für Kunstgeschichte, 69 (4), 541-547 [in English].
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[Integration of Digital Art into Traditional Artistic Environment]. Bulletin jf the Sout Ural State University. Series:
Social Sciences and the Humanities, 15(4), 100-107 [in Russian].
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Tsuhorka, O. P. (2015). Obrazotvorche mystetstvo i mozhlyvosti novitnikh tekhnolohii [Fine arts and the capabilities of
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Viber, Zh. (1961). Zhivopis i ee sredstva [Painting and its means]. Izdatelstvo Akademii khudozhestv SSSR [in Russian].
Zatserkovnyi, V. I., & Karevina, N. P. (2014). Aerokosmichni doslidzhennia Zemli: istoriia rozvytku [Aerospace land:
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The article was received by the editorial ofce: 27.04.2020
Совгира Тетяна Ігорівна
Кандидат мистецтвознавства, старший викладач,
Київський національний університет
культури і мистецтв, Київ, Україна
Мета дослідження
–
на основі аналізу творів сучасного візуального мистецтва, створених з використанням
цифрових технологій, з’ясувати специфіку їх застосування та виявити співвідношення традиційного й інноваційного
методів в сучасному живописі; вияснити спосіб нанесення фарби та функціональний складник 3D-друку у процесі
«виробництва» живописних полотен. Методологічна база дослідження становить комплекс кількох методів:
аналітичного
–
для розгляду історичної та мистецтвознавчої літератури, теоретично-концептуального методу
–
для характеристики понятійно-термінологічної системи дослідження, а також порівняльно-типологічного
–
для
порівняння традиційних технологій живопису з інноваційними цифровими. Наукова новизна дослідження полягає
у висвітленні специфіки запровадження цифрових технологій у візуальне мистецтво. Висновки. Виявлено, що за
допомогою технології «штучного інтелекту» можна відтворити втрачені фрагменти зображень. Встановлено, що
завдяки технології тривимірного друку можливе не лише виготовлення копій, а й створення авторських художніх
композиції. Виявлено, що на основі алгоритмічного аналізу та математичного моделювання можна встановити
співвідношення знакових систем музичних і живописних творів та на основі виявлених результатів алгоритмічного
обчислення встановити певне співвідношення виразних засобів мистецтв в цифровому (математичному) еквіваленті.
Отже, завдяки «штучному інтелекту» можливе синтезування різних видів мистецтва в одному творі та використання
методів різних галузей знань. Проаналізувавши факти впровадження цифрових технологій, алгоритмічного аналізу
живописних полотен і технології 3D-друку, можна констатувати той факт, що алгоритмічне мистецтво знаходиться
лише на першій стадії свого розвитку та має значні перспективи в майбутньому.
Ключові слова: цифрова технологія; живопис; техніка; алгоритмічне мистецтво; генеративна нейромережа
Совгира Татьяна Игоревна
Кандидат искусствоведения, старший преподаватель,
Киевский национальный университет
культуры и искусств, Киев, Украина
Цель исследования
–
на основе анализа произведений современного визуального искусства с использованием
цифровых технологий выяснить специфику их использования и выявить соотношение традиционного и инновационного
методов в современной живописи; рассмотреть способ нанесения краски и функциональную составляющую
3D-печати в процессе «производства» живописных полотен. Методологическая база исследования представляет
собой комплекс нескольких методов: аналитического
–
для рассмотрения исторической и искусствоведческой
литературы, теоретико-концептуального метода
–
для характеристики понятийно-терминологической системы
исследования, а также сравнительно-типологического
–
для сравнения традиционных технологий живописи
с инновацийними цифровыми. Научная новизна исследования заключается в освещенни специфики внедрения
цифровых технологий в визуальное исскуство. Выводы. Выявлено, что с помощью технологии «искусственного
интеллекта» можно восстановить утерянные фрагменты изображения. Выяснено, что за счет технологии трехмерной
печати возможно не только изготавливать копии, а и создавать авторские художественные композиции. Выявлено,
что за счет алгоритмического анализа и математического моделирования можно установить соотношение знаковых
систем музыкальных и живописных произведений и на основе полученных результатов алгоритмического вычисления
выяснено определенное соотношение средств выразительности искусств в цифровом (математическом) эквиваленте.
Таким образом, за счет «искусственного интеллекта» возможно синтезирование разных видов искусства в одном
произведении и использование методов разных областей знаний. Проанализировав факты внедрения цифровых
ЦИФРОВІ ТЕХНОЛОГІЇ В СУЧАСНОМУ
ВІЗУАЛЬНОМУ МИСТЕЦТВІ
ЦИФРОВЫЕ ТЕХНОЛОГИИ
В СОВРЕМЕННОМ ВИЗУАЛЬНОМ
ИСКУССТВЕ
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ISSN 2410-1176 (Print) • Вісник КНУКіМ. Серія: Мистецтвознавство. Вип. 42 • ISSN 2616-4183 (Online)
ІСТОРІЯ ТА ТЕОРІЯ МИСТЕЦТВА
технологий, алгоритмического анализа живописных полотен и технологии 3D-печати, можно констатировать тот
факт, что алгоритмическое искусство находится лишь на первой стадии своего развития и имеет значительные
перспективы в будущем.
Ключевые слова: цифровая технология; живопись; техника; алгоритмическое искусство; генеративная
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