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It seems to me that UV space could help here. For those unfamiliar, UV
mapping maps each point on the surface of an object to a point on a plane
with axes called u and v. In MegaPov, UV mapping is used to wrap a texture
around an object, and a UV mapper already exists for most primitives (not
pathological shapes like julia fractals) and for meshes. To find a point on
the surface near a given point, map the original point into UV space,
perturb the UV point a small amount, and then map back from UV onto the
object. As long as the UV map works, this point is guaranteed to be on the
surface of the object, no matter how convoluted the shape is.
"Mael" <mae### [at] hotmail com> wrote in message
news:3bcd8e6d$1@news.povray.org...
> > > hmm yes , but i m pretty sure bad situations will arise, for points
near
> the
> > > edge of a cube for instance
> > >
> >
> > As i understood the paper, these problems can be avoided by always using
> > the same distance for calculating the diffusion term instead of using
the
> > individual distance of each sample. It also says this is likely to
> > produce some inaccuracy but it seems to work quite well.
>
> i was not clear (sorry for my pathetic english, i wish i could draw a
little
> example :)
> the problem is not for calculating the contribution of a sample but rather
> to find the points which will contribute
> how do you find points on the surface of the object , assuming the surface
> is flat (but knowing this is not true) ?
>
> M
>
>
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