That one's pretty neat too, although in that context (specific target image) it seems like you could do it more directly than black-box optimization. The problem could be posed as something like: given N (overlappable) polygons, what is the way of coloring and arranging them that most closely matches the target image? That should be directly specifiable in a mathematical-optimization framework, and then you'd vary N to get different aesthetic properties.
With the face example, black-box optimization might be the only practical choice, though, since the face-detection component is probably not easy to express in a nice mathematical form.
