Lecture 13: Global Illumination & Path Tracing (84)
ericlu28
Using Russian Roulette is intuitive because we can also calculate the expected number of function calls (1/probability of stopping), which will be finite so long as probability is non-zero.
brandonlouie
Another thing to note is that you want to chose your probability of stopping to be just small enough that you can get an adequate number of samples, but not too small such that you never terminate.
jerrymby
A reply for the above comment: from my understanding, I think it always terminates no matter how small the stopping probability is as long as it's above zero. Because if you take it to the limit, the probability of never terminate is (1-p)^inf which approaches to zero.
cvankeuren
Will the Russian roulette method of stopping recursive light bouncing always yield the best result on average? I'm assuming that we can come up with ideal stopping points for specific rays in a specific image, but I'm curious if theres any kind of optimized random algorithm that yield better results on average.
dhruvchowdhary
@cvankeuren Russian Roulette is an effective method for managing recursion in ray tracing, but I think it doesn't guarantee the best result for every case. The performance of this method can vary based on the scene's complexity and how light is distributed. Optimized algorithms may outperform it in specific cases by adjusting the stopping probability based on the scene's characteristics or the ray's contribution to the final image. This would create a balance between computational efficiency and rendering accuracy.
myxamediyar
It is interesting that for a lot of complicated problems, monte carlo intergration-like solutions always seems to help. I wonder if you can use probability simulate other graphic's related phenomena - like fluids
andrewn3672
Russian Roulette is a simple and easy to understand way of termination for global illumination. Because it's impossible to know when we should stop bouncing light, the easiest way would just to have a random probability of terminating the bounce recursion.
Using Russian Roulette is intuitive because we can also calculate the expected number of function calls (1/probability of stopping), which will be finite so long as probability is non-zero.
Another thing to note is that you want to chose your probability of stopping to be just small enough that you can get an adequate number of samples, but not too small such that you never terminate.
A reply for the above comment: from my understanding, I think it always terminates no matter how small the stopping probability is as long as it's above zero. Because if you take it to the limit, the probability of never terminate is (1-p)^inf which approaches to zero.
Will the Russian roulette method of stopping recursive light bouncing always yield the best result on average? I'm assuming that we can come up with ideal stopping points for specific rays in a specific image, but I'm curious if theres any kind of optimized random algorithm that yield better results on average.
@cvankeuren Russian Roulette is an effective method for managing recursion in ray tracing, but I think it doesn't guarantee the best result for every case. The performance of this method can vary based on the scene's complexity and how light is distributed. Optimized algorithms may outperform it in specific cases by adjusting the stopping probability based on the scene's characteristics or the ray's contribution to the final image. This would create a balance between computational efficiency and rendering accuracy.
It is interesting that for a lot of complicated problems, monte carlo intergration-like solutions always seems to help. I wonder if you can use probability simulate other graphic's related phenomena - like fluids
Russian Roulette is a simple and easy to understand way of termination for global illumination. Because it's impossible to know when we should stop bouncing light, the easiest way would just to have a random probability of terminating the bounce recursion.