# Overview of global illumination in Tomasz’s kajiya renderer

Soon after showcasing his recent rendering results which left industry veterans impressed and causing many of us to start documenting ourselves about ReSTIR, professional madman Tomasz Stachowiak showed a new demonstration of the global illumination capabilities of his pet project.

But more importantly, he took the time to describe the techniques used to get such results. The writing is fairly high level, and assumes the reader to be familiar with several advanced topics, but it comes with clear illustrations at least for some parts. It also mentions the various ways in which ReSTIR is leveraged to support the techniques used. Finally, it doesn’t try to hide the parts where the techniques fall short, quite the opposite.

The article: Global Illumination overview.

In very brief, the rendering combines a geometry pass, from which a ReSTIR pass is done to compute the first bounce rays, in combination with a sparse voxel grid based irradiance cache for the rest of the light paths, which also relies on ReSTIR, and a few clever tricks to handle various corner cases, as well as denoising and temporal anti-aliasing to smooth things out.

Recently a short video from dark magic programmer Tomasz Stachowiak made the rounds in the graphics programming community, at the sound of jaws hitting the floor in its wake. It shows his recent progress on in his renderer pet project: beautiful real-time global illumination with fast convergence and barely any noise, in a static environment with dynamic lighting.

In a Twitter thread where he discussed some details, one keyword in particular caught my attention: ReSTIR.

ReSTIR stands for “Reservoir-based Spatio-Temporal Importance Resampling” and is a sampling technique published at SIGGRAPH 2020 and getting refined since.

## The original publication

Spatiotemporal reservoir resampling for real-time ray tracing with dynamic direct lighting
The publication page includes the recording of the SIGGRAPH presentation, with a well articulated explanation of the technique by main author Benedikt Bitterli.
(same publication hosted on the NVidia website).

## Improvements over the original publication

After the initial publication, NVidia published a refined version producing images with less noise at a lower cost, which they call “RTXDI” (for RTX Direct Illumination).

## Other limitations

When discussing on Twitter some of the limitations of ReSTIR, Chris Wyman made the following remarks:

To be clear, right now, ReSTIR is a box of razor blades without handles (or a box of unlabeled knobs). It’s extremely powerful, but you have to know what you’re doing. It is not intuitive, if your existing perspective is traditional Monte Carlo (or real-time) sampling techniques.

People sometimes think SIGGRAPH paper = solved. Nope. We’ve learned a lot since the first paper, and our direct lighting is a lot more stable with that knowledge. We’re still learning how to do it well on full-length paths.

And there’s a bunch of edge cases, even in direct lighting, that we know how to solve but haven’t had time to write them up, polish, and demo.

We haven’t actually tried to solve the extra noise at disocclusions in (what I think of as) a very principled way. Right now a world-space structure is probably the best way. I’m pretty sure it can be done without a (formal) world-space structure, just “more ReSTIR.”

# Building an artificial window

Several years ago, I mentioned the Italian company CoeLux, which specializes in making artificial windows: light fixtures that look like sunlight in a clear blue sky.

The price of their products is apparently in the range of several tens of thousands of dollars (I’ve heard prices like $20k to 50k), which makes it out of reach for most individuals. Not many details about their invention are available either (from the promotion material: LED powered, several hundred watts of electrical power, a solid diffuse material, and a thickness around 1 meter), and I was left wondering what was the secret sauce to their intriguing technology. The YouTube channel DIY Perks has been working on day light projects for a while now, improving at each iteration. Yesterday they published a video explaining how to build a light that seems to give very similar results as CoeLux’s product, from some basic materials that are fairly simple to find. Since their solution takes roughly the same volume, it’s tempting to think it uses the same technique It’s extremely satisfying to finally see how this works and, despite the practical aspects, quite tempting to try if only to see how it looks in real life. # Intersection of a ray and a plane I previously showed the derivation of how to determine the intersection of a plane and a cone. At the time I had to solve that equation, so after doing so I decided to publish it for anyone to use. Given the positive feedback, it seems this was useful, so I might as well continue with a few more. Here is probably the most basic intersection: a ray and a plane. Solving it is straightforward, which I hope can be seen below. Like last time, I am using vector notation. 1. We define a ray with its origin$O$and its direction as a unit vector$\hat{D}$. Any point$X$on the ray at a signed distance$t$from the origin of the ray verifies:$\vec{X} = \vec{O} + t\vec{D}$. When$t$is positive$X$is in the direction of the ray, and when$t$is negative$X$is in the opposite direction. 2. We define a plane with a point$S$on that plane and the normal unit vector$\hat{N}$, perpendicular to the plane. The distance between any point$X$and the plane is$d = \lvert (\vec{X} – \vec{S}) \cdot \vec{N} \rvert$. If this equality is not obvious for you, you can think of it as the distance between$X$and$S$along the$\vec{N}$direction. When$d=0$, it means$X$is on the plane itself. 3. We define$P$the intersection or the ray and the plane, and which we are interested in finding. Since$P$is both on the ray and on the plane, we can write: $$\left\{ \begin{array}{l} \vec{P}=\vec{O} + t\vec{D} \\ \lvert (\vec{P} – \vec{S}) \cdot \vec{N} \rvert = 0 \end{array} \right.$$ Because the distance$d$from the plane is$0$, the absolute value is irrelevant here. We can just write: $$\left\{ \begin{array}{l} \vec{P}=\vec{O} + t\vec{D} \\ (\vec{P} – \vec{S}) \cdot \vec{N} = 0 \end{array} \right.$$ All we have to do is replace$P$with$\vec{O} + t\vec{D}$in the second equation, and reorder the terms to get$t$on one side. $$(\vec{O} + t\vec{D} – \vec{S}) \cdot \vec{N} = 0$$ $$\vec{O} \cdot \vec{N} + t\vec{D} \cdot \vec{N} – \vec{S} \cdot \vec{N} = 0$$ $$t\vec{D} \cdot \vec{N} = \vec{S} \cdot \vec{N} – \vec{O} \cdot \vec{N}$$ $$t = \frac{(\vec{S} – \vec{O}) \cdot \vec{N}}{ \vec{D} \cdot \vec{N} }$$ A question to ask ourselves is: what about the division by$0$? Looking at the diagram, we can see that$\vec{D} \cdot \vec{N} = 0$means the ray is parallel to the plane, and there is no solution unless$O$is already on the plane. Otherwise, the ray intersects the plane for the value of$t$written above. That’s it, we’re done. Note: There are several, equivalent, ways of representing a plane. If your plane is not defined by a point$S$and a normal vector$\hat{N}$, but rather with a distance to the origin$s$and a normal vector$\hat{N}$, you can notice that$s = \vec{S} \cdot \vec{N}$and simplify the result above, which becomes: $$t = \frac{s – \vec{O} \cdot \vec{N}}{ \vec{D} \cdot \vec{N} }$$ ## Signed distance to a plane For the sake of simplicity, in the above we defined the distance to the plane as an absolute value. It is possible however to define it as a signed value:$d = (\vec{X} – \vec{S}) \cdot \vec{N}$. In this case$d>0$means$X$is somewhere on the side of the plane pointed by$\vec{N}$, while$d<0$means$X\$ is on the opposite side of the plane.

Distances that can be negative are called signed distances, and they are a foundation of Signed Distance Fields (SDF).

# Interview with competitive live coders

Last week my friend LLB and I wrote an article about live coding. Or rather, given what the task consisted in, it would be more accurate to say that we copy-pasted the answers of six interviewees until the order felt right.

In their comments, they remember how and when they’ve discovered live coding and got involved, explain how they prepare for a competition, talk about their state of mind during a match, share their esteem for fellow live coders, and reflect on this new kind of e-sport.

You can read them here: A new e-sport: live coding competitions.

# Implementing a Physically Based Shading without locking yourself in

Over the last few months I have been trying to push my understanding of Physically Based Shading, by actively exploring every corner and turning over every stone, to uncover any area where I lack knowledge. Although this is still an ongoing process and I still have a lot to do, I thought I could already share some of what I have learned in the process.

Last weekend the Easter demoparty event Revision took place, as an online version due to the current pandemic situation. There, I presented a talk on Physically Based Shading, in which I went into electromagnetism, existing models, and an brief overview of a prototype I am working on.

The presentation goes into a lot of detail about interaction of light with matter from a physics point of view, then builds its way up to the Cook-Torrance specular BRDF model. The diffuse BRDF and the Image Based Lighting were skipped due to time constraints. I am considering doing a Part 2 to address those topics, but I haven’t decided anything yet.

## Abstract

How do you implement a Physically Based Shading for your demos yet keep the possibility to try something completely different without having to rewrite everything?
In this talk we will first get an intuitive understanding of what makes matter look the way it looks, with as much detail as we can given the time we have. We will then see how this is modeled by a BRDF (Bidirectional Reflectance Distribution Function) and review some of the available models.
We will also see what makes it challenging for design and for real-time implementation. Finally we will discuss a possible implementation that allows to experiment with different models, can work in a variety of cases, and remains compatible with size coding constraints.

## Slides

Here are the slides, together with the text of the talk and the link to the references:
Implementing a Physically Based Shading model without locking yourself in.

## Video

And finally here is the recording of the talk, including a quick demonstration of the prototype:

Here is the shader used during the presentation to illustrate light interaction at the interface between to media:

## Acknowledgements

Thanks again to Alan Wolfe for reviewing the text, Alkama for the motivation and questions upfront and help in the video department, Scoup and the Revision crew for organizing the seminars, Ronny and Siana for the help in the sound department, and everyone who provided feedback on my previous article on Physically Based Shading.

FWIW – I think the model of refraction by the electromagnetic field causing electrons to oscillate is the better one. This explains not only refraction but reflection as well, and even total internal reflection. Feynman does out the wave calculations: https://feynmanlectures.caltech.edu/II_33.html

It also explains better IMO why a light wave keeps its direction in a material. If an atom absorbs and re-emits the photon there is no reason why it should be going in the same direction as before (conservation of momentum is maintained if the atom recoils). Besides which, the lifetime of an excited atomic state is many orders of magnitude longer than the time needed for a light wave to propagate across the diameter of the atom (even at an IOR-reduced speed).

Moreover, in the comments of the shader above, CG researcher Fabrice Neyret mentioned a presentation of his from 2019, which lists interactions of light with matter: Colors of the universe.
Quoting his summarized comment:

In short: the notion of photons (and their speed) in matter is a macroscopic deceiving representation, since it’s about interference between incident and reactive fields (reemitted by the dipoles, at least for dielectrics).

# From Maxwell’s equations to Fresnel’s equations

This series of short videos shows how to derive Maxwell’s equations all the way to Fresnel’s equations. Each one is about 10 to 15mn long.

The first four videos show how to use boundary conditions to deduce the relationship between the electromagnetic field on both sides of a surface (or interface between two different media).

The next four videos use the previous results to obtain the Fresnel equations, for S-polarized and P-polarized cases.

The rest of the series then dives into other topics like thin film interference.

The series assumes the viewer to be already familiar with the Maxwell equations, so it can be helpful to first see the explanation by Grant Sanderson of 3Blue1Brown on Maxwell’s equations.