It turns out I don't know nearly as much as I thought I did about Monte Carlo. I did realize that it was a way of estimating the integation of all the incoming light at a certain point, but apparently that's way higher level than I realized.
So, Jonathan (another lab mate) set me to reading a few chapters about Monte Carlo from a book I actually already own (Physically Based Ray Tracing). My bad for not having read it sooner. It turns out that you use the summation above (roughly) to estimate the integral based on samples that conform to a given probability density function (PDF). So, Jonathan thought that it might be a good idea for me to work on adding Monte Carlo summation to my currently existing ray tracer. While I was doing that I ran into some problems with some extra factors of π in my equations. It was at this point Jonathan realized that my education in radiometry was also sorely lacking!
Poor Jonathan, I'm sure he expected the person who was showing up to know all this stuff already, but he's been very nice about it. He's taken the same approach I took with undergrads in my OpenGL class, 'teaching it to you helps me to learn it better', but I still feel kind of bad about it. Although it's TONS of fun to be learning all this stuff and spending the whole day tinkering with my ray tracer.
2 comments:
I felt smart for about the first line, because I know the Monte Carlo formula. The feeling didn't last long because I had no idea of it application to incoming light. Glad to hear that something other than WoW is fun to you...just kidding. Good luck with the ray tracer
Well when I first heard them talk about it I didn't feel so smart. This is all stuff I should already know (even Chuck thought so when I talked to him this morning - he's visiting cuz he's on Guillaume's PhD Jury).
But I'm learning lots, and I just hope I can repay them by actually getting a paper finished on this Bayesian stuff.
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