Link to blog post by Roger Alsing
50 semi-transparent polygons, with vertex locations and color being determined by a genetic algorithm - evaluation function is a comparison to the actual Mona Lisa.
What's instructive here is the simplicity of the model: 4 parameters per polygon - 3 vertices and the color, for a total of 200 parameters. I'm guessing the evaluation consists of summing all the polygons and then doing some kind of image comparison - wonder how fast it runs?
The final result appears after close to a million iterations...but recognizable image occurs around 100,000 generations. Also, comments point out that the algorithm does not appear to be a standard "genetic" algorithm, but instead a stochastic hill-climbing algorithm.
Update:
FAQ by Roger Alsing
Source code
A Clojure version of the same approach
Another update:
A very detailed look at optimizing this image compression approach
Monday, December 8, 2008
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