<p>The most usual way of employing Russian roulette in path tracing is to cut paths with high attenuation (low throughput) without adding bias into the resulting estimator, which would occur if you just use constant maximum path length. </p>

<p>Although Russian roulette incorporates additional variance into the resulting estimator, it helps throwing away long paths consuming a lot of processing power while contributing little into the resulting image, possibly leading to increased performance of a renderer.</p>

CC BY-SA 4.0
2019-12-02T16:30:31.757Z
2019-12-02T16:30:31.757Z
ivokabel
<p>Why should we use Russian Roulette? Does it reduce ray tracing artifacts? </p>

CC BY-SA 4.0
2019-11-28T20:49:50.143Z
It makes your image unbiased. Which means you can average it with other unbiased images of the same scene to get better results. In general it increases variance, but also efficiency.
lightxbulb
CC BY-SA 4.0
2019-11-28T22:15:40.290Z
Also see [this question](https://computergraphics.stackexchange.com/questions/2316/is-russian-roulette-really-the-answer)
Hubble
<pathtracing>
Why is Russian Roulette used in ray tracing?
bitWise
# Why is Russian Roulette used in ray tracing?

(Asked by: username_0 on 2019-11-28)

Why should we use Russian Roulette? Does it reduce ray tracing artifacts?

**Tags:** pathtracing

> **Comments:**
> **username_1**: It makes your image unbiased. Which means you can average it with other unbiased images of the same scene to get better results. In general it increases variance, but also efficiency.  
> **username_2**: Also see [this question](https://computergraphics.stackexchange.com/questions/2316/is-russian-roulette-really-the-answer)  

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## 1 answers

### Answer by username_3 on 2019-12-02. Score: 2

The most usual way of employing Russian roulette in path tracing is to cut paths with high attenuation (low throughput) without adding bias into the resulting estimator, which would occur if you just use constant maximum path length.

Although Russian roulette incorporates additional variance into the resulting estimator, it helps throwing away long paths consuming a lot of processing power while contributing little into the resulting image, possibly leading to increased performance of a renderer.


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