Probes are not in the "grid", i want to place them manually on specific places, so i want to use "K nearest probes" approach as described in article.

I was thinking i should use distance from object as weight, tho i would not take too distant probes in calculation, so number of probes could vary.

If i use "triangulate" approach i need to always interpolate between 3 probes?

Barycentric coordinates gives me 2 values, how can i interpret this as one is needed for lerp function?

My bad, I didn't actually read the article

But now I've taken a glance at the article. The "tetrahedralization" method is the 3d variant of what I suggested with triangles. I'll keep talking about triangles, because it's not fundamentally different, just simpler to talk about. Barycentric coordinates on a triangle gives you two coordinates, and the third coordinate is 1 - coord1 - coord2. With barycentric coordinates you wouldn't be using a lerp function directly, though you would implement something that is essentially equivalent. What you must do with barycentric coordinates is a *linear combination* of the three triangle vertices (ie the three probes) using the barycentric coords. So, in effect:

InterpolatedProbe = Probe1*coord1 + Probe2*coord2 + Probe3*(1 - coord1 - coord);

In the above code InterpolatedProbe is a linear combination of Probe1, Probe2 and Probe3 using coord1, coord2 and (1 - coord1 - coord2) as the coefficients. The lerp function is actually a special case of a linear combination (and in even more specific terms, lerp is actually interpolating using barycentric coordinates in one dimension).

But anyway. Triangulating or tetraherdalizing your probe network might be somewhat difficult, so maybe the K nearest probes method would be a better first pass. I'm not entirely sure what the author is imagining, but I suspect he's figuring people will calculate their interpolated probe as a linear combination of the K closest probes, possibly using distance as a weight and normalizing by the total weights of all K probes. In code:

float weight(Vector3 position, Probe p)
{
float maxDist = 10.0f;
return max(0, maxDist - length(p.position - position));
}
InterpolatedProbe = weight(pos, probe[0])*probe[0] +
weight(pos, probe[1])*probe[1] +
...
weight(pos, probe[k])*probe[k];
float totalWeight = weight(pos, probe[0]) + ... + weight(pos, probe[k]);
InterpolatedProbe /= totalWeight;

That's just off the top of my head. It's a linear combination of K probes, though I obviously have no idea how it would look. And you can write the weighting function however you want.

**Edited by Samith, 09 August 2014 - 01:11 PM.**