Reading Veach’s Thesis, Part 2
In this post, we’re continuing to read Eric Veach’s doctoral thesis. In our last installment, we covered the first half of the thesis, dealing with theoretical foundations for Monte Carlo rendering. This time we’re tackling chapters 8–9, including one of the key algorithms this thesis is famous for: multiple importance sampling. Without further ado, let’s tuck in!
As before, this isn’t going to be a comprehensive review of everything in the thesis—it’s just a selection of things that made me go “oh, that’s cool”, or “huh! I didn’t know that”.