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In a BRDF or NDF this most likely refers to a spherical Gaussian distribution, also known as a von Mises–Fisher distribution. It's similar to the usual Gaussian, but using the dot product between two unit vectors as a measure of distance to the mean: $$ p(\hat v) = a \exp(\lambda(\hat \mu \cdot \hat v))$$ where $a$ is a normalization factor, $\lambda$ is ...


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Having a gaussian lobe usually means that your ndf is one or a weighted sum of gaussian distributions. Instead of your ndf, you can define your brdf in the same way. A gaussian distribution is a function of the form $$\frac{1}{\sigma\sqrt{2\pi}} e^{-\frac{(x-\mu)^2}{2\sigma^2}}$$ It has a hat shape common to many ndfs; this is good because it mimicks how ...


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