Using math to study paintings to learn more about the evolution of art history
Oct 2020, phys.org
Here's a great description of how the program works:
The work involved digitally scanning 14,912 paintings—all of which (except for two) were painted by Western artists. The data for each of the paintings was then sent through a mathematical algorithm that drew partitions on the digital images based on contrasting colors. The researchers ran the algorithm on each painting multiple times, each time creating more partitions. As an example, the first run of the algorithm might have simply created two partitions on a painting—everything on land, and everything in the sky. The second might have split the land into buildings in one partition and farmland in another.
Conclusions? The horizon line has gone up since the 17th century (from halfway to one-third), and using two horizon lines became more common over time, and abstract art isn't compositionally biased to either the horizontal or the vertical. They also have less large-scale partitions. Think Pollock's drip-paintings and allover De Koonings). They call it lack of macroscopic structure. Also, all this transcends nationality. Doesn't matter where you're from, we're all sipping the same juice.
They also note however that the trends they see could also be a curatorial thing, where the dataset they're using, large as it is, was chosen by someone to be in each book they used, hence their collective bias.
Image credit: My favorite horizon line of all time -- Piet Mondrian, Dune Landscape, 1911
Notes:
Byunghwee Lee et al. Dissecting landscape art history with information theory, Proceedings of the National Academy of Sciences (2020). DOI: 10.1073/pnas.2011927117
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