Florian Pesth wrote:

> > Not necessarily, as calculating the best distribution of triangles among
> >the vertex points can be a very slow thing to do (sounds a bit like an
> >exponential-time problem).
> First I have to find an algorithm, that works., than the PC can run a week,
> or so... ;)

Have a look at:

http://astronomy.swin.edu.au/pbourke/modelling/polygonise/

All you need from your problem to this approach is an evaluation function
which compute the proximity of a 3D position to your array of point.
The closer the higher value is probably the way to go,

A function that would do it would be like Sum/i(Proximity[i])
where Proximity[i] is = 1/(distance between position and vertex i)
Or even the square of it, so as to avoid the square root computation,

Sum has the interesting effect that the more points are closer, the bigger 
the tesselated sphere.
If you do not like that effect, you can use Max/i(proximity[i]) instead.
(or just Min/i(Distance[i]) which is nearly the same).

P.S.: Proximity should be maxed when position and vertex are identical
      (when distance is smaller than a fixed value).

P.S.2: Beware of USA patent if it can apply to you...

P.S.3: the isovalue to use depends on your choice for the function.
        Sum: tricky, Min or Max : easier.

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

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