Lecture 13: Global Illumination & Path Tracing (81)
mylinhvu11
The theory of using N bounces to increase efficiency and not solve for values when the data is so minuscule that it won't affect the final image. However, what factors or determinants are needed to determine the N value and how does it change with each situational? I'm assuming renderings with less light would have a lower N value since less light would be bouncing in the environment.
starptr
We don't choose N, we instead use random termination by having some probability prr of terminating at the next bounce. See the slide 3 slides after this one
The theory of using N bounces to increase efficiency and not solve for values when the data is so minuscule that it won't affect the final image. However, what factors or determinants are needed to determine the N value and how does it change with each situational? I'm assuming renderings with less light would have a lower N value since less light would be bouncing in the environment.
We don't choose N, we instead use random termination by having some probability prr of terminating at the next bounce. See the slide 3 slides after this one