AI Arts vs. Conventional Arts (2): Color Language of AI Paintings vs. That of Pointillism

By Eric S. Shi, 21-Jul-2021, updated 2-Nov-2021

Pointillism and G. Seurat

When it comes to post-impressionism art, Georges-Pierre Seurat, the French artist, and the initiator of the post-impressionism movement is probably the most prominent cornerstone of the grandeur monument. The famous Pointillistic painting style (also narrowly known as chromoluminarism), the flag of the post-impressionism movement, was devised by Seurat, single-handedly.

Seurat was, up to his time, one of the very few painters who spent a lot of time studying color theories and applying them to his painting practice. His innovative works such as, “A Sunday Afternoon on the Island of La Grande Jatte” and “Le Chahut”, altered the direction of modern art, and collectively became one of the icons of late 19th-century painting.

The formation of Seurat’s Pointillism (and the broader post-impressionism developed from it) was probably most influenced by the color theory developed by M. E. Chevreul, a French chemist. Chevreul discovered that if two colors were juxtaposed very closely, they could “synthesize” another color in human eyes when seen from a distance. Chevreul also recognized that a "halo" color can be “produced” after staring at a color for a while, where the “halo” color is the opposing color (also known as a contrast color and/or complementary color) in the color wheel. For example: after looking at a red object, one may see a cyan echo/halo color around the original object. This imaginary formation of the contrast color is later explained as a result of retinal persistence.

O. Rood also exerted influence on the formation of Pointillism. Rood pointed out that the juxtaposition of primary hues (e.g., red, green, and blue-violet) next to each other would create a far more intense and far more pleasing color, when perceived by the human eyes, than the physical mixing of corresponding color pigments would. Before Pointillism, painters only knew the latter method, i.e., to create the color (or a hue) by mixing two or more other colors (or hues).

Rood also pointed out the difference between additive and subtractive qualities of color, since pigments and light do not mix in the same way:

· Pigments: Red + Yellow + Blue = Black

· Light: Red + Green + Blue = White

Seurat took these color theories to his heart and came to believe the color theorists' notions on scientific approaches to paintings. He believed that just like a musician could use counterpoint and variation to create 1D harmony in music, a painter could create 2D harmony on canvas, using hues and shades. Seurat came to believe that color theories at his time were like a universal law, and he was driven to prove that the knowledge of perception and optical laws could be used to create a new language of art based on its own set of heuristics and he set out to show this language using lines, color intensity and color schemes. Seurat called this language chromoluminarism, later more popularly known as Pointillism which in turn initiated a movement known as post-impressionism across the whole horizon of visual art and music and literature.

The essence of Pointillism theories includes the following:

1. The emotion of joy can be liberated by the establishment of a predominance of luminous hues (i.e., the warm colors) and by the use of lines pointing upward.

2. Calm can be established by the balanced deployment of light color vs. dark color, warm color vs. cold color, and horizontal lines.

3. Sadness can be enhanced by using dark and cold colors and by lines directed downward.

The key vocabularies of the Pointillistic color language include: juxtapose, color dot, predominance, hues, visual blending, emotion.

In the art world of the 19th century, Pointillism represented a major paradigm shift, liberating oil painting (which was nearly synonymous with art) from a handicraftsman skill to something that can be guided by physical science. It was very much admired as a revolution in art by elites of society in a wide period, of 19th – 21st centuries.

For instance, Seurat’s “A Sunday Afternoon on the Island of La Grande Jatte” was so stimulating, it inspired Stephen Sondheim and James Lapine to produce the famous musical, “Sunday in the Park with George” and later a book by James Lapine.

The musical was so successful, it won the 1985 Pulitzer Prize for Drama, 1985 Drama Desk Outstanding Musical, 1985 Drama Desk Outstanding Book, 1985 Drama Desk Outstanding Lyrics, 1991 Laurence Olivier Award for Best New Musical, and 2007 Olivier Outstanding Musical, among others.

Compare Pointillist paintings with AI paintings

The fact that both the Pointillist and AI paintings are constituted of color dots makes their comparison sensible. Seurat deserves all the above-mentioned honors, and much more, especially in the context of painting practices and tools of the 19th – 20th centuries.

However, as the artists living in the dawn of an AI age, with various types of computer tools and capabilities available, does it make sense to question ourselves on: how can we do better than the past masters? AI-augmented painting is, at least, one of the possible answers. The comparison below, hopeful, will demonstrate that AI painting does have certain merits and hold promises.

Figures 1 and 2 compare an AI painting “API0029 《Taming the Monster, Saluting Seurat’s Le Chahut》” by Eric S. Shi (Source of Figure 1: https://www.esandag-ai-art-studio.com) and a famous Pointillist painting “Le Chahut” by G. Seurat (Source of Figure 2: https://en.wikipedia.org/wiki/Le_Chahut).

From the comparison, it is clear that AI painting holds promises at least in the following areas:

(1) In deploying color (hue) gradients: Although both painters, on Figure 1 and Figure 2, approached their respective themes similarly and built corresponding images with blocks of color dots, e.g., in hats, in faces, necks, and arms, and in costumes, the colors in Figure 1 command more depths and variations and are consequently more fluid and emotional.

Such fluidity and sensation are a direct consequence of establishing a color gradient field in the AI painting. AI is advantageous, as compared to human brains, in calculating complex 2D arrays of gradients, sorting out quantitative details of the gradient fields (e.g., where the local maximums and/or local minimums of color intensities should be positioned, and how sharp the changes in vectorial gradients should be implemented going from a local minimum to a local maximum, or vice versa), and then iteratively alternating all these to optimize.

To this end, the shadows on legs (or stockings), music instruments, and the suit worn by the music conductor (to the lower-left corner) in Figure 2 are plainly colored in darker brown against less dark brown. Although efforts were made in setting up sorts of color gradients in painting shadows of lampshades on the wall where dark blue juxtaposed with the dark brown of different grey scales were employed, the colors remained dull and obtuse. Comparatively, when AI is tasked to resolve a similar shadow problem, the colors came out more vivid and more imaginative, as manifested in Figure 1.

(2) In handling signs of the gradients across borderlines of the color blocks: When two color blocks (or dots), say R (for red) and B (for blue), are placed adjacent to each other, several scenarios may emerge:

a. Both R and B approach their common borderline with increasing color intensity. We call this an R+ vs. B+ scenario. (The plus sign comes from the second-order differential of the color intensity being positive.)

b. Both R and B approach their common borderline with decreasing color intensity. We call this an R- vs. B- scenario. (The minus sign comes from the second-order differential of the color intensity being negative.)

c. R approaches the borderline with increasing color intensity whereas B approaches the same borderline with decreasing color intensity. We call this an R+ vs. B- scenario.

d. R approaches the borderline with decreasing color intensity whereas B approaches the same borderline with increasing color intensity. We call this an R- vs. B+ scenario.

Depending on relative positions of R and B in the color wheel, the relative brightness (i.e., the greyscale) of R and B, and relative positions of R and B on the "temperature" scale (e.g., a moderate warm color vs. a very cold color), the above 4 scenarios may leave the audience with different emotional impressions, e.g., confliction, harmony, clear, confusion, lively, dull, …… Precise execution of a master color scheme incorporating quantitatively correct combinations of coherent deployments (vectorial orders) of the scenarios a – d, across hundreds or even thousands of color pairs in a painting, holds the key to the success of a painting.

Planning of such a precise master color scheme, precise execution of the master plan, and remembering everything in between have proven a set of tasks too heavy for human brains which are very much analog in nature.

The new vocabularies that AI brought into the color language include color gradient field, the 2D array of vectorial color gradient, differential gradient field, and 2nd order vectorial color gradient field.

It is not surprising, that Seurat often needed to work out multiples of studies before he released a final painting. For example, it took him 2 years and c.a. 60 studies to complete his famous “A Sunday Afternoon on the Island of La Grande Jatte”.

On the contrary, such a task is very suitable for AI which is digital in nature, with practically infinite memory capacities.

On a similar token, we can revisit the doctrines of the Pointillism listed in paragraph 6 of this article, in the context of capabilities offered by AI. For instance, the Pointillist theory points out that the emotion of joy can be created by the predominance of luminous hues (i.e., the warm colors), which is correct. However, if we stop there, we would have missed a big opportunity unintentionally. AI points out this big opportunity to us.

Figures 3 and 4 compare the iconic Pointillist painting “A Sunday Afternoon on the Island of La Grande Jatte” by G. Seurat (Source of Figure 3: https://en.wikipedia.org/wiki/A_Sunday_Afternoon_on_the_Island_of_La_Grande_Jatte) and an AI painting “API0048 《Color of Dusk in Barcelona · an AI’s View》” by Eric S. Shi (Source of Figure 4: https://www.esandag-ai-art-studio.com).

For a long time, the “A Sunday Afternoon on the Island of La Grande Jatte” has served as a textbook example to illustrate the Pointillist theory, where a large percentage area of the canvas that is covered with warm colors (e.g., greenish-yellow and pink in Figure 3), and sharp contrast (e.g., the sharp lines dividing the sun-shined lawn and shadowed areas in Figure 3) were deployed to make the painting look bright and joyful.

Granted, Figure 3 does deliver a bright and joyful scene, especially in the context of visual art in the 19th – 20th centuries. However, in the context of an AI age of the 21st century, if Figure 3 is compared with Figure 4, we can't help but notice that what Figure 3 delivered is not at the apex of what a painting can deliver. Using similar or smaller percentage area of warm colors (e.g., yellow, greenish-yellow, and red), and less sharp contrast, but empowered by a properly designed color gradient field, Figure 4 has managed to create a higher level of joyful emotion, although not necessarily at the ultimate apex.

Figures 5 and 6 are included here to add more visual illustrations of the concept of the color gradient field.

1. Similar to Pointillist paintings, AI paintings of Figures 1, 4, 5, and 6 have optimal viewing distance. To capture the overall color effect, views are recommended to step back far enough until the color dots are no longer discernable to naked eyes. If the paintings are viewed on a computer screen, the recommended size of an image is roughly 5% of the view field (or roughly 5% of a computer screen).

2. As the viewing distance is reduced continuously (or as the image is enlarged on a computer screen, e.g., to 20% of the screen or larger), a viewer may start to feel dizzy visually. Such a dizzy feeling is caused by the color gradient field(s). The technique of juxtaposing color dots, as deployed by the Pointillist artists, also effectively results in the color gradient field(s), although the Pointillist artists neither recognized it nor termed it as such.

3. The color gradient fields resulting from the simple juxtaposition of color dots are the simplest type of color gradient fields. They are made of simple 2D repetitions of certain color pairs (or color triplets). Mathematically, such a simple juxtaposition array of color dots can be represented either by a repetitive 2D pulse array or by a simple 2D sinusoidal function. For instance, in Figure 3, the grass fields under sunshine are all made of certain shades of yellow and green color dots. Comparatively, the color gradient fields established in Figures 1, 4, 5, and 6 are much more complex. Consequently, the colors are more vivid, the optimal viewing distances are longer, and the visual dizziness effect is more pronounced for these AI-painting, as compared to the Pointillist paintings.

Figure 5 Figure 6

Figure 5: An AI painting “API0055 《Impression of Oasis》” by Eric S. Shi (Source: https://www.esandag-ai-art-studio.com).

Figure 6: An AI painting “API0058 《Return from Grazing》” by Eric S. Shi (Source: https://www.esandag-ai-art-studio.com).

Conclusion

(1) The color language used in the Pointillist paintings can be enriched and expanded, as empowered by AI, to include new kernels such as color gradient field (i.e., 2D arrays of vectorial color gradients) and differential gradient field (i.e., 2D arrays of the 2nd order vectorial color gradients), to enhance the emotional impact and aesthetic values of visual arts (e.g., paintings), among other purposes.

(2) AI (digital and precise) and human brains (analog and qualitative) can augment each other. AI can help to clear the thick fog of mathematical computations to enable humans to see the possibilities that humans have failed to see in the past thousands of years. For a human artist living in the dawn of an AI era, energy should no longer be wasted on trying to compete with AI or channeled into a denial mode(s). The correct question that we should continue to ask is: how can we best embrace AI and use it to augment us in our creative endeavors.

(Written by Eric S. Shi, @ www.esandag-ai-art-studio.com)