The Mona Lisa, Genetically (and Digitally) Evolved

Roger Alsing’s project “Genetic Programming: Mona Lisa” shows simple, transparent polygons gradually evolving into one of the more subtle and intricate compositions in art history: the Mona Lisa’s face.

Alsing created a program that renders polygons in increasingly complex combinations, using code that mimics the mutation of DNA to shift the combinations ever so slightly in continuous iterations. The program then compares the iteration to an image of the Mona Lisa, and if it looks more like the painting than the last iteration, it moves on, and mutates again. Only the best mutations, as judged by their similarity to Leonardo’s canvas, survive.

The artist gave himself a limit of 50 polygons to recreate the Mona Lisa, which seems like quite a challenge. In fact, it took 904,314 generations to come up with the final result, which kind of looks like what Lyonel Feininger might do with the iconic portrait. See the full process below.

Roger Alsing’s evolution of Mona Lisa (All images via the artist)

It may be from 2008, but Alsing’s work takes on a new significance in the context of the recent discussion around the New Aesthetic, the new aesthetic vocabulary that sees art encountering technology. The polygonated Mona Lisa was organically replicated by a digital process; it takes one of the most famous works in the canon of Western art history and distorts it through a computational lens. Visual art can now be replicated infinitely, transposed into any style and format. Alsing points to the fundamental mutability of all images, famous or not.

See some of his other polygonated images below, though these are definitely on the kitschy side of things. They don’t strike me as quite so compelling as the Mona Lisa, but then few works of visual art are up to that challenge.

Munch’s “Scream,” polygonated
The Sydney Opera House, polygonated
On the totally kitsch side of things, a dog, polygonated

See more of Roger Alsing’s work on his website.

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