Christoph Hormann wrote:
> How about adaptive (curvature or distance dependant) methods.  See for
> example:
> 
> http://www.cs.queensu.ca/home/jstewart/papers/cga01.html

From Page 2:
The algorithm requires an evaluator for the implicit function defined at all points in
space, 
an evaluator for the function gradient defined at points near the surface, 
and a bounding box around the surface.

The bounding box, we have.
Alas, the only function available is "Insideness test", and the result is only 0 or 1
 (usually).
So, no easy way to have an evaluator for the gradient (we could make one based
on soft variation of the value of the implicit function, if the answer was smoother).

But even requiring each Pov-object to provide this kind of function is probably not
worth it, because of the various transformation that might apply to an object.
Anyway, try getting a smooth evaluation for a julia_fractal, it might be possible
but really horrible.

The link may nevertheless be of interest for optimisation of the parametric object,
which I do not know.

-- 
Non Sine Numine
http://grimbert.cjb.net/
Puis, s'il advient d'un peu triompher, par hasard,

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