Mtg 15/26: Tue-04-Mar-2025

Outline for Today

Shapes (Chapter 6), Ray Tracing Videos

Administration

Today

if you didn’t submit your Assignment 1 last week, you have until 23:59 today to submit (and receive a late penalty)
exams will be graded before our next Tuesday meeting (watch for email from gradescope.com) and will be discussed then
there is an opportunity to give me 2 kinds of feedback: your formative evaluation of the class so far (under the Exams topic on UR Courses) – this is anonymous – and your evaluation of the fairness of the midterm (under the Participation topic on UR Courses) – not anonymous, since it is counted towards participation
Videos by Eric Haines:
- Part 1
- Part 2
- Part 3
- Part 4
- Part 5
- Part 6
- Part 7

For Next Meeting

read the rest of Chapter 6
Take quiz before the start of our next meeting

Wiki

Link to the UR Courses wiki page for this meeting

Media

Transcript

Audio Transcript

Okay, I think that's working.
All right, so we're eating 15
of 26 so it's our first meeting in March. You
I haven't heard that expression for March in like a blank and
out like a blank. They're different blanks. I
so if it starts out being mild, it's going to be go out being
not very nice. It's not it's going to end being not very
nice. And if it is not very nice to begin with, it'll be nice by
the end of the month. I don't know that this is still accurate
in this era of climate change, but that just came to mind,
so maybe There are other ways to update that
old saying and it anyway. So I just wanted to I noticed there
were some people who hadn't submitted assignment one. So if
you want to get a mark with a late penalty submitted by the by
midnight tonight, after that, you won't get a you won't be
able to get a mark for it. So the exams will be graded before
our next Tuesday meeting. So you'll get an email from grade
scope.com because I'm going to scan I'm scanning the exams, and
so I have the PDFs, and you'll get a copy of the scan PDF with
type notes, so it may be a little more legible than my
handwriting and a little bit more organized perhaps.
Anyway, it's
so I'll be using that so you'll get an email, and you'll get it
before next Tuesday, so you can, if you have questions, you can
use grade scope to ask questions about the marks and so on. So
it's got a lot of nice features, I think. So
there's that, so
there's an opportunity to give me two kinds of feedback. I'll
just point you down here. I'm
so formative feedback at midterm for formative feedback for me,
it's under exams. I'm not sure when I've set the cutoff time
for this. I let me check. Maybe
I'll make this to Six instead. So Thursday,
I Okay, and then
the other one is feedback about the midterm exam. What
did I make this one for? I
i mean that Friday can Make the other One Friday. I
so the formative feedback for me, that's anonymous, but this
last one, so this one is anonymous, the formative
feedback at midterm, and then this one is not anonymous,
because it's part of participation. Okay, so
So I came across when I was looking for exam question,
making up the exam questions last week, I came across some
videos by Eric Haynes, who's a an engineer at Nvidia, and who I
met. I many, many years ago at the SIGGRAPH conference. And he
was, I associate him with this sphere flake. I
so I see that he has he created a set of videos about ray
tracing that I thought might be interesting to look at.
So if I turn the lights down, we can watch some videos and
I see if I've done this properly.
Hi, my name is Eric Haynes, and I'm an engineer, and we're going
to do a series of audio entries
to do it. This is David Kirk, who's a fellow, says There's an
old joke that goes ray tracing is the technology. I the
technology.
You analogy of
the future, and it always will be well the future is now here,
as of least 2018 that a single NVIDIA card, terrain card, can
now do real time ray tracing. Let's start with the basics.
What's a ray? Well, a ray is defined by just two things. It
has an origin, some point in space, x, y, z and a direction.
And ray casting is the idea of taking that Ray and shooting it
out in that direction and finding what gets hit. And this
is not in a rendering algorithm. It's just a basic tool in the
toolbox. You can use it however you want. You can be using it
for checking radiation or doing all kinds of other things. We
use it for rendering. So ray casting is just shooting a ray
out and seeing where it hits something. You can also use ray
casting between two points. So you may say, Well, I've got a
point A, point B, and I shoot a ray, and I want to see if
anything's in between. This could be used, for example, if I
want to see if there's a shadow. If you already have the points
like a and b, there's a light and a surface that you can shoot
that Ray, and if anything gets in the way, then you know that
point B is in shadow. Ray casting is a way that you can
actually make an image. So if you think of a screen like a
screen door, and you think of each little square on that
screen door that you're looking through, think of that that's
your pixel. So you want to know what's at that pixel and what
the ray hits. So the ray shoots through that pixel and goes up
into the environment and hits a bunch of things, and whatever is
closest is what you're going to see through that pixel. And then
you can shoot rays towards the lake, for example, and see if
you have hit or missed anything in between. And if you've hit
something, then the objects, your point of intersection is in
shadow, otherwise it's lit. And this is actually the first use
of ray tracing in a computational form, is for by
this person at Apple back in 1968 he traced rays towards
lights to get shadows. And his outfit device was a pen plotter,
a pen that draws on a big sheet of paper. So Ray tracing really
takes off back in 1980 with the seminal paper by Turner with it,
it covers a lot of interesting basic things that we still do
nowadays, like anti aliasing and bounding, vying hierarchies,
which I'll talk about in a minute. But basically he has
this intuition, or this idea of, how can I get reflections and
refractions and shadows, and how can I do this in kind of a
recursive way? That's the big breakthrough. So let's show how
that works. Here we're shooting ray from the eye again, and it
hits a piece of glass. So this glass is nice and shiny, so it's
reflective and it's also refractive. So we might first
shoot a shadow ray, and the ray goes towards the light. OK,
good. That's eliminated. But we also do this thing, which is to
spawn off two more rays, one in the reflection direction going
down below, and one in a refraction direction going
through the glass. So we can follow both of these rays. I'll
ignore the one going off the screen, the reflection
direction, one, the refraction one. Then we shoot another
shadow ray and see again, the effect of the light. And then
again, we spawn more rays. We can shoot a reflection, if
there's an internal reflection Ray that's going upwards. And
again, we'll kind of ignore how further it bounces and shoots up
more rays. So we'll just follow the refraction one that's going
off to the right. So then when going off to the right, it's
that box. And again, we can shoot a shadow ray, and that one
actually is blocked, so we know that the box is in shadow. So
with that, we now take all those contributions, all those
intersection points, the two on the glass and the one on the
box, and we kind of add them all up, and we get a color at the
eye. We get all color for the pixel. So that's wooded style
ray tracing. It's really good for things like sharp shadows
and reflections and refractions. The advantage of this kind of
rendering algorithm is that you can basically do it from the
eye. You know that you are hitting a mirror surface, and it
goes to the light, and you basically get a very few number
of rays that you need to cast, versus if you had sort of shut
all the rays from the light, and had it bounced around, and
almost all those rays are not going to actually get to the so
the next breakthrough as far as Ray tracing goes is these Cook
stochastic, or sometimes called distribution ray tracing in 1984
The idea here is that instead of shooting just a single
reflection Ray, for example, you might have a glossy surface,
something with kind of a sheen, and you shoot a sort of a burst
of a rays. Instead, you can also get cool effects like motion
blur. And the idea here is just that instead of shooting one
reflection Ray, you're shooting a bunch. Or instead of shooting
one shadow ray, you're shooting a bunch to try to get a soft
shadow with stochastic ray tracing, you shoot a ray out. It
hits the box, and then you shoot one ray at the area light. So
our sun now is a little bit larger to give it some actual
area, just like the real sun. And we picked some arbitrary
point on that sun. This one made it all the way to the light. And
here's two more rays, one hit, one missed. So now we know at
this point that two thirds of our rays are hitting the area
light, and so we can say, well, OK, the shadows somewhat soft,
two thirds illuminated, but we can shoot more and more and more
rays and get a better answer. So this is stochastic ray tracing.
And the idea here is, like, I say, just shooting burst arrays,
it's more expensive. You have to shoot more rays, and the more
rays you shoot, the better the answer you get. But that's, you
know, it's often worth the cost. So in 1986 was sort of the next
theoretical leap, which is kijiya style, diffuse, inter
reflection. And this is a paper, a classic paper, which we'll go
to in a further lecture, in a later lecture, called the
rendering equation. And basically his idea is, well, you
know what? If we say the sky is the limit, we're just going to
shoot rays out from the eye, and we're going to have each ray hit
something, and we don't necessarily know which way it's
going to reflect. It's a mirror. We know, sure, or reflect on the
mirror direction. But say it's something like unglazed pottery
or some other thing like cement or something, you then don't
really know which way the lights coming from. Well, you know the
lights coming from all kinds of different directions. So what
you do is you shoot more rays in different directions, but with
path tracing, you shoot just one ray in one direction and follow
it along a path. So let's, let's show you what that looks like.
So here's path tracing where we shot one ray through, you know,
through our pixel, and it's in one particular location in the
pixel. It hits this box, and we shoot a secondary ray in some
direction, and it goes off to the sky. Say, we shoot another
ray that one happens to hit a light. So that's actually going
to be a fairly important contribution to sort of a lot of
direct illumination from the sun. And notice that we've also
put the pixel sample in a slightly different location
within the pixel. This allows you to get sort of anti
aliasing, kind of for free, because by moving the samples
around within the pixel, you're basically sampling the whole
box, the whole pixel box, instead of just the center of
the pixel. And so we go. We continue here. Here's a path
where we hit the ground, and then it hit the cylinder, and
then it shot up down to the ground, somewhere else and so
on. You keep shooting these rays, and you get more and more
paths. And once you have all the paths, then all meaning you're
tired of shooting rays, you basically then add up all those
contributions. You basically have figured out where the
lights coming from for a bunch of different directions, a bunch
of different paths, and add them up and get a color. So in the
film industry, for example, you'll often see scenes where
they'll use 1000 rays, 3000 rays per pixel, and so those take a
little while to compute. The point is, is that by doing this,
you will eventually get the right answer. You know, it's
sort of reversing the whole process of getting light
percolating through the system and but doing it just from the
eye, and you will eventually get the right answer. So that's path
tracing. And what makes ray tracing great is the fact that
it can be that simple. It's just you're shooting a ray and
bouncing it around along different paths. And here's a
ray tracer, in fact, that's on the back of a business card.
This is from Paul Ekberg business card when he was at
Pixar in the 80s. And it actually is a ray tracer. It
will actually make a little ray traced scene with, I think it's
shooting against a bunch of spheres. So it's a very compact,
simple kind of algorithm. You have this simple tool, a ray and
using those rays in various great ways. So you can basically
get beautiful results like this, where you're getting soft
shadows and lovely reflections. And that's it for this lesson. I
wanted to point at some further resources that you'll see on the
web page links to places where you can find books, and there's
also going to be a link for ray tracing gems, which is a book
that I helped co edit, so thanks, and I'll catch you at
the next lecture.
Hi. My name is Eric Haynes at Nvidia, and this lecture is
rasterization versus ray tracing to start with. I'd like to have
a quote, and this one is the brute force approach is
ridiculously expensive. This is from a very long paper, I think
it's 5060, odd pages long, a seminal paper about hidden
surface algorithms. And the interesting thing about this
quote is it's from appendix B, and they talk about this
algorithm, they go, Well, this algorithm is ridiculous. It's
going to use up a quarter of a megabyte. Who has $60,000 for
that much memory, and it turns out to be the one that GPUs now
use all the time. It's called the Z buffer. Sometimes it's
just a matter of brute force winning out. And rasterization
has been quite successful with this algorithm for, you know,
for decades now. And the difference between rasterization
and ray tracing is pretty simple. In rasterization, what
we're doing is we're taking a grid and we're kind of throwing
objects at that grid of pixels, and for each object, we
basically look at each pixel that that object covers, and
says, Well, is the object closer in this point or not? And if it
is closer, we save it. If not, then we discard in ray tracing.
We flip that loop, we go for each pixel, and we go for each
object, then, does the object cover that pixel? So in other
words, at a pixel, we shoot a ray, and we look at each object
and we find out which is the closest one, if any. So let's
just zip through rasterization, just to make sure we're all on
the same page. Here's three triangles. That's sort of the
ultimate image that we want to form, but we're only using the
centers of pixels, so we're not going to get anything that high
res. So you start with an empty grid, you throw a red triangle
against it, and you cover the pixels that are where the
triangle covers the center of the pixel. Now you take the
triangle away, and let's get the next triangle in. Here's a green
triangle, and again, you cover the ones that it covers. And the
trick is, as the green triangle is in front of the red triangle,
so we know that any pixels that it covers will also cover the
red triangle. Finally, we have this blue triangle. It's behind
the green and the red triangle. So when we cover its pixels, we
both say, oh, OK, is the pixel covered by this triangle? Yes,
oh. But we also store for each of those pixels a depth, and if
the depth says, Oh, I already have something there, and it's
closer than discard. So the blue is further away, only the pixels
that are not covered by written green get covered by the blue.
With ray tracing, as I say, we reverse the process. We start
shooting rays. And as we go, we basically are hitting various
objects. So at this point, we hit a red and a blue triangle,
and the red triangle is closer, so that's the one that shades
the pixel. And we keep through this process, and we hit green
triangles and red and so on. And as we go, we now go through the
whole process and we get the same answer. We get the same
image as the rasterizer. The thing that makes ray tracing
particularly useful as the scenes get larger and larger and
more complex is something called the bounding volume hierarchy.
So with the bounding volume hierarchy, what you're doing is
you have a circle that encloses your whole scene, and within
that, then there are other circles, within circles, within
circles, and on down the tree until you get to actual objects.
And this has a great advantage for ray tracing, because you
shoot a ray against that structure, and it can be
extremely efficient. So for example, if the ray doesn't hit
the outer circle at all, then we're done. We don't have to
look at any of the circles within circles, because we know
we haven't hit the outer circle. But if we hit that outer circle,
what we do is we open it up and we look at the two children
circles, and we shoot the ray against those, and not down the
chain until either we hit something or we're clearly not
going to hit anything. We're out of circles to shoot against. And
so this process tends to be order log n in computer science
terms. In other words, it's faster than just throwing all
the objects against the ray. So instead of shooting you know, a
ray against a million objects. You may shoot a ray against only
a very few objects, because those are the only ones that are
close enough to the ray that there's any chance that it's
going to hit. Here's another view of that kind of algorithm,
and it's more kind of what we actually really do in ray
tracing, which is to use bounding boxes. So here we have
a hierarchy of boxes, and as we go on down the chain, we
basically are looking in those boxes, and then there's sub
boxes and sub sub boxes. And eventually we find out, okay,
that one box has a bunch of triangles in it, and, oh, look,
the ray hit that one triangle. So instead of shooting the ray
against 1000 triangles, we might shoot it against a handful of
boxes and a few little few triangles. And that's it. So
it's much more efficient. Interestingly enough, this used
to be the reason that people thought, Well, Ray tracing is
going to totally beat rasterization back in the 80s,
like they thought, OK, this is it. Look we have this order log
n rasterization. Well, look for rasterization. We have to throw
every triangle against the screen. So that's going to be
order n, and being the number of objects in the scene. However,
rasterization has a bunch of ways that it can do the same
kinds of tricks and so on that allow you to get sort of order
log n behavior. So that's not really a great argument. And
this slide is rasterization and ray tracing, and compares the
two. And I'm not going to go through it, but you can look at
it, you can put pause and try to see what all the differences
are. But the real point is here is that they're kind of just
complimentary. They're two different ways of looking at the
same rendering system. Is that you want to make a picture,
well, what's an efficient way to do it? Well, with Ray tracing,
you are shooting rays. With rasterization, you're throwing
triangles on the screen. The key here is that it really isn't
rasterization versus ray tracing. Rasterization is really
good at situations where there's a point and like such as a high
point or a light and you want to look out into the scene, and
you're happy to get a nice regular grid, or pixels or
whatever, and have these samples at a regular distance and so on.
And Ray tracing is much more general, and that you can take
from any point to any point and see what's in between or what's
along that ray. So they each have their strengths, and they
can be used together doing so you get wonderful images like
this, where the eye rays are all rasterized. We're basically
using rasterization to get our initial view of the world, and
then we're using ray tracing to get all the lovely glossy
effects and lighting effects. And that's the end of this
lesson. So I do want to point you to resources on our website
which give links to all kinds of great stuff about ray tracing,
including free books that you can get. One of those free books
is ray tracing gems, which is all about modern practice. It's
downloadable for free. It's a PDF. Hi, my name is Eric hings,
and I'm an engineer at Nvidia, and we're going to do a series
of lectures about ray tracing. The first one is the basics of
ray tracing. Let's get going the thing I like to do it in it. I
knew that
was too good to be true. I
Eric, hi. My name is Eric Haynes with Nvidia, and this talk is
called ray tracing hardware. So I'd like to open these talks
with a little quote, and this one I love, which is, pretty
soon computers will be fast. That's kind of always the case,
right? It's like, oh, with just a little more power, I could do
this new, cool thing, but I think there's like a constant,
which is that Windows will always take five seconds to open
a new window, no matter what Ray tracing is, one of those
processes that's what we call embarrassingly parallel. Since
you're calculating a color at each different pixel, each
different pixel is independent of the other pixels. So you
could throw a processor at each one. Turner witted famously came
up with this idea of, well, what if we took a football field and
filled it full of Cray computers, and we put light
bulbs on the top of each one, red, green and blue, and we just
had each computer compute a single pixel, and then we fly a
blimp over it, so we can see the image produced in 1987 is the
first ray tracing machine that I ever saw. It's the at&t pixel
machine. It was kind of a surprise to me to hear about
this, like when I arrived at SIGGRAPH and oh, whoa, there's
this machine that's doing ray tracing. And it was doing these
scenes where I had just come up with this database for testing
Ray tracers. Procedural database is what it's called. And so
there's one image sphere flake, which they were using to test
and would take me hours to render one of these little
scenes. And for them, it was taking 30 seconds. And with
tuning a year later, it was taking them just 16 seconds to
run on this machine. Now this machine, admittedly cost
hundreds of 1000s of dollars, and is now sort of a footnote in
history. It was very expensive for the time. Nonetheless, was
the first one where I saw real life ray tracing, and better
yet, I saw real time ray tracing. They had a tiny little
postage stamp on the screen, little 64 by 64 pixel kind of
thing, maybe 32 by 32 and they had a case where you could move
the mouse and move this sphere on top of this desktop kind of
thing, or on top of a plane, and it would reflect things in real
time. And now we can run that on, you know, the crummiest cell
phone, but at the time, it was just magic. So Moore's law is
ending. Sad to say, it's not just a few people saying it
this. It's one of those things that people said for years, oh,
Moore's law is just about to end. However, the sign that's
actually kind of being true. It's where, you know, we're
hearing it from Nvidia, we're hearing it from Google, and
we're hearing it from other companies. That there's just not
as much of an oomph every year from the previous year. So what
that means is we have to rethink how we designed hardware. Where
we're going in, Nvidia is considering more special purpose
hardware. If you think about transistors, there's basically a
bunch of transistors on the chip, and it's your budget. It's
how many you can use for things. You can use it for memory. You
can use them for general CPU kind of processors, or you can
use it for something special purpose. So on GPUs, on
traditional GPUs, we have special purpose hardware for
rasterization. With this new generation Turing, we now have
special purpose hardware for both artificial intelligence,
deep learning operations and for ray tracing, and so they're
called RT cores for ray tracing, and that's what we're going to
talk about next. So RT cores, or ray tracing cores, perform two
basic functions. They accelerate Ray bounding, volume hierarchy
traversal and Ray triangle intersection. So with traversal,
they are basically shooting the ray against a bunch of boxes,
and they return the boxes that they hit with Ray triangle.
They're shooting against a bunch of triangles. And there's sort
of these two levels where you can basically have a mesh and
have that mesh be copied as many times as you want, because it
just has a hierarchy on is triangles, so you get this
instancing, so it could have lots of bunnies for very little
extra cost. And we use string multi processors, which are
shader cores for doing other kinds of instancing or custom
intersection, like Ray Sphere or Ray subdivision surface, and for
traditional shading. The other thing that's been interesting is
to see how much memory has changed over the years. It used
to be we'd have some small number of megabytes, you know,
maybe 100 megabytes, if we're lucky, and it's gone up to the
point where we're now having machines that have as many as
512 gigabytes. And film production uses, for example,
scenes that are maybe 50 gigabytes or more, for very
complicated scenes. So we're within the realm of actually
being able to hold entire scenes from a film inside GPU memory.
And so this lets us do things like Ray tracing, where we kind
of have to have all the data around at the at the same time,
or at least most of the data, and be able to swap data in as
needed. So the idea here is just that we can now store things
like a whole ray tracing database and do something with
it. Back in the old days, we could only store, not very much
at all, a few textures, a few triangle meshes, maybe, if we're
lucky. So for example, to just show the speed up that you can
get, this is from Metro Exodus and just an analysis of one of
their frames. So in the Pascal architecture the previous
generation, it took someone so much time in Turing if you
didn't use ray tracing, the ray tracing cores, but did use some
of the improved functionality in Turing otherwise, like integer
math, you could trace rays against boxes and so on in an
efficient manner, and it would save you some time. Then
finally, though, if you turn on these ray tracing cores, it
takes that center chunk and just squishes it right down to a very
small footprint as far as how much time it's actually taking.
And the other good news is that you can do a lot of tuning. It's
one thing to make the hardware, but as we saw with the 18 T
pixel machine, where they started at 30 seconds per frame
and went down to 16 after a year of tuning. Well, the same thing
can happens with games or any other applications, where as you
learn the hardware and you learn what the problems are, you can
get faster and faster. So over just a few months time, we're
able to have a considerable increase in the speed for
Battlefield five. For example, Nvidia developed a demo with ILM
and Unreal engine called Star Wars reflections in March 2018
we were able to present this along with Microsoft's
announcement of DirectX for ray tracing, we used four volta
water cool GPUs to run this in real time. What was great was,
just a few months later, when Turing came out, we could run
this all on just one GPU. Back in 1987 I was astounded to see
the 18 T pixel machine doing my 512 by 512 image of 8000 spheres
running in just 30 seconds of frame. Now in a Turing class, I
can run the same demo at 5 million spheres and gets 60
frames per second. No problems. To see the full Star Wars
reflections demo, or to find other resources about ray
tracing. Come to our website. You can also get the full ray
tracing gems book for free as a download.
Let me try this again.
Hi. My name is Eric hings, and I'm an engineer at Nvidia, and
we're going to do a series of lectures about ray tracing. The
first one is the basics of ray tracing. Let's get going. The
thing I like to do in any of these lectures is give a little
quote at the beginning. And this is David Kirk, who's a fellow Ed
you
Hi. My name is Eric Haynes with Nvidia, and this talk is about
the ray tracing pipeline. I'd like to start with a quote, and
this one's from Matt far around year, 2008 GPUs are the only
type of parallel processor that has ever seen widespread
success, because developers generally don't know they are
parallel. Rasterization and ray tracing both make use of
parallelism. Rasterization is straightforward in that you send
a triangle to the screen, you do vertex shading, you do pixel
shading, and then whatever the result is, you do a raster
operation to blend it into the screen. With ray tracing, we
have a similar kind of flow. You start with a ray, you traverse
the environment, and then you shade it. However, at this
point, we actually have the ability to recurse, to go back
to the beginning and shoot more rays, to spawn off more
possibilities, such as shadow rays or reflection rays. This
bottom part in the green box is what we actually do with RTX
acceleration is we can do that traversal and intersection piece
very rapidly. In DirectX for ray tracing, and in Vulkan for ray
tracing, there are five new kinds of shaders that are added.
There's a ray generation shader. And what that does is it's kind
of the manager. It basically starts the rate going and keeps
track of it and gets its final result. There are intersection
shaders. So if you wanted to intersect a sphere, you'd have
an intersection shader for that, or a subdivision surface, or
whatever you want. There's a different kind of shader for
each one. Then there's these last three shaders which are
sort of a group. There's a miss shader which says, Well, I shot
a ray and it didn't hit anything. What do I get? There's
a closest hit shader, which is, well, I hit something. What
shall I do with it? Kind of a traditional shader, but you can
also spawn off rays at that point, such as reflection or
shadow. And there's also any hit shaders, which I'll talk a
little bit more about in a second. So just to sum up again,
we have the ray generation shader, which controls all the
shaders. There's the intersection shader, which
essentially defines the object shape. And there are these
control per Ray behavior shaders Miss closest hit and any hit. So
how do these fit together? Well, there's the complicated, many
boxes, kind of version here. Here's the simple version of
that same flow chart. What we do is we have a trace ray which is
called to generate the ray, and then it goes into this
acceleration structure loop where we walk through the
bounding volume hierarchy and find out objects that could
potentially be hit by the ray. The intersection shader is then
applied to that object, and if we hit and it's the closest hit,
we keep track of that information. We also then use
the any hit shader if available for testing, if the object is
transparent and the ray should actually just continue on. Once
we get through this traversal loop, we eventually get to the
end where there's nothing else in the acceleration structure to
hit. It's gone through the whole bounding volume parking, and now
we take our closest hit and say, Okay, what's that shader S, or
if we missed everything, then we use our Miss shader and that's
what color we get back for the pixel. The any head shader I
wanted to talk about a little bit more. It's an optional
shader. It's one that basically is used for transparency. So
mention, you have this leaf on the right, which you're doing a
tree of leaves, and so you're not really caring about each
individual leaf. So you really just take a rectangle and you
put a texture of a leaf on it. Now, much of that texture is
empty, it's blank, it's transparent. So what the any hit
shader does is it goes and checks the texture. So let's say
I hit with my ray in the upper left hand corner of that
rectangle, the any hit shader would say, Oh well, that's
transparent. So don't really count this as a hit, and let's
just keep going so real time ray tracing can clearly be used for
games. Here are three shipping titles that are showing
reflections, global illumination and shadows. What's also cool
about real time ray tracing, or interactive ray tracing,
accelerated ray tracing, is that you can use it for all kinds of
other things. For example, you can do faster baking. Baking is
where you shoot lots and lots of rays. It's an offline process
that takes a bit and you basically bake the results into
a bunch of texture maps. I was reading about how one studio
went from 14 minutes of bake time to 16 seconds of bake time
once they switched over to GPU ray tracing, even if you don't
want to use ray tracing, particularly in your title, you
can use it for a ground truth test. Shaders that are part of
the Direct X can be used on any machine. You can basically put
your shaders into a ray tracer and get the correct answer. So
if you're trying to do some approximation, you can always
get the ground truth and know what you're aiming for, and then
back off and try to figure out what your faster method might
be. The other cool thing you can do with Ray tracing hardware is
that you can abuse it. In other words, we're now looking into
researching ideas of what else can we do with this. Could we do
collision detection, or could we do volume rendering, or could we
do other kinds of queries? And work is just starting on this,
and I think it's a really interesting open field where
there's all kinds of possible ways we can use and abuse the
new hardware. And that's it for this talk, for more information
about ray tracing and plenty of other good free resources such
as free books. Go to this website. You can also get a free
book that's very modern. What
do you think so far? I
really like the spheres. Yeah,
hi, my name is Eric Haynes. I'm with Nvidia, and this talk is
about ray tracing effects. It's got all the eye candy you would
ever want. I like to start with a quote, and I promise I won't
try to sing it. This is from Queen and it's from Bohemian
Rhapsody. Is this the real life? Is this just fantasy? And I like
to say that because which one is real of these two images, one is
a photo and one is the simulation. Turns out the one on
the one on the left is the photo and the one on the right is the
simulation. This is the famous Cornell Box. The Cornell Box was
actually made in 1984 I believe it was actually at the lab at
the time. In fact, they're not part of that group. And it was
pretty funny because Don Greenberg comes in and he goes,
Okay, guys, we're going to make a box. And they're like, Yeah,
sure, I can do that with a little computer graphic. He's
like, no, no, we're going to get some plywood. And you're gonna
get some paint. And they were all like, what are we doing? But
eventually, you know, they got with the program, and the rest
is history. So with the Cornell Box, what you can do is start
with a really simplified system and look at the various effects.
So we're gonna start with just hard shadows here. And so
instead of an area light source. Overhead, we have just a point
light source, a single point where the light's emitting. You
can see that what you get is these very sharp shadows. And a
sharp shadow is just going from some intersection point, some
point what we're looking at to the light. And some of those
will be blocked, and those are in shadows, and some are
illuminated. If you want soft shadows, you have to go with an
area light where you're sampling on various points on the light.
So this is that more stochastic ray tracing, kind of a feel,
where you're shooting a bunch of rays, and you're figuring out
what percentage of the light you see if you're fully in light,
great, if you're partially in light, that's called the
penumbra, and that's where the soft shadow is. Or if every ray
is blocked, then you're in the Umbra full shadow area. The next
step is to start bouncing that light around, to let the light
percolate through the environment. So instead of just
looking directly at the light, we're going to have light that
bounces around. This is called by a lot of different names.
There's inter reflection, because the light's reflecting
off of a bunch of surfaces, or indirect lighting or color
bleeding, which is sort of specifically where color comes
off of one wall and illuminates something else. And they all
have this group term called Global Illumination. So in this
case, we can see a ray is going from the floor where there's a
green spot, and hits the wall and it goes to the light. There
are, in fact, tons of paths. This is one of many, many paths,
if it could hit the wall and go towards the light, and all of
them contribute a green color to that floor area. In that last
scene, everything was diffuse, matte. Didn't really have any
kind of reflection to it. You can also go with glossy
reflections, where, again, you're doing that stochastic
kind of process, where you're shooting a ray in a burst, like
you're shooting a burst of rays from your reflective surface,
and that gives you this fuzzy, softer reflection in it. So
those are a bunch of different kinds of effects. And here's
another example of glossy reflection. It's very shiny on
the left and goes to more and more rough as we go to the
right. So here's your quiz question. This image has a
number of effects in it. Which effects that we've talked about.
Do you see in this image? The three that I see are there's
glossy reflections on the ceiling and on the floor and on
the wall to the right, there's inter reflection throughout, and
there's soft shadows. And I especially want to note the
inter reflection throughout. The point of this is that if you
were to just have this seam lit by just the sun, you would only
have a few small portions of the interior that would actually get
any light at all. The rest of the interior would just be
entirely dark. So by having this light bouncing around the
interior, we get a realistic look to things. There are other
operations you can do with Ray tracing where it's not
particularly physically based, but it's physically plausible.
So this is called ambient occlusion, where there's no
particular light source in this scene. But what we're doing is
we're shooting out little bursts of rays from every location in
the scene, and trying to see if things are in crevices or could
be occluded by other objects. So let's look at that scooter in
particular with ambient occlusion. What you do is you
take a point and you shoot out a burst of rays, and you shoot
them a certain distance. You may shoot them, say three feet or
whatever scale makes sense for your scene. If a bunch of rays
hit something like underneath the scooter or the tire or
whatever, then we can say that, well, this area is kind of dark
like odds are that if a light were to be shown upon the
scooter, that area would be in shadow. On the other hand, if
you're out in the open, you have a burst of rays, and almost all
the rays get to that maximum distance, like three feet, or
whatever it is, and maybe a rare to hit something. But overall,
you're kind of in the light, and you can see it all, so that area
gets no shadow at all. So notice that it's a term that's not
physical in that if you actually shown the light underneath the
scooter, it would still look dark using ambient occlusion,
but it's a really good approximation of how crevices
darken up and so on. And so it's commonly used in games, and it's
been used in rasterization for a long time, but with Ray tracing,
you can get a better answer. Basically. Another cool thing
you can do with Ray tracing is depth of field, you can get a
background blur, as in this shot, or you can get a
foreground blur, or you can get Foreground and Background blurs.
For that matter, the idea is that by using depth of field,
it's a very cinematic effect, and you can lead the user's eye
to whatever point you want to focus on, so the character on
the right in this case, the other thing you can do is motion
blur, instead of varying where the rays go, what you're doing
is varying where the model is in time, and you just kind of add
up the rays at various points during the frame, and you get
this blurry effect. And again, this is a cinematic effect, and
it's actually quite important to have in games or films, because
what you want to do is you want to sort of not have this kind of
stroboscopic effect, where, if you just had a single flat frame
with very sharp edges and so on, it animates as if someone is
flashing a strobe light on the scene. This can actually be used
in various films, like gladiator for effect, but generally it's
not the effect you want. And when the film is actually
running, you don't tend to see this motion blur so much. It
just looks natural. You can also do atmospheric effects. So if
you have, say, a beam of light, you can do a thing called Ray
marching, where the ray hits the beam and marches through it, and
it looks at light scattering in and light scattering out, and so
on. And you just kind of walk through that thing and sample it
as you go. And you can get these nice beams of light, God Ray,
kinds of effects. So I'm going to just show this short clip
from Minecraft RTX, a demo we're making in conjunction with
Microsoft of bringing ray tracing to Minecraft. And I'll
just leave it as sort of a quiz question for you as to figure
out which effects are happening in this little demo you
one last effect I want to talk about is caustics, which sounds
dangerous. It sounds like acid or something, and they are
dangerous, and not because of the octopus in the picture here,
what caustics are is the reflection of light off the
surface of water, or refraction of the light through water or
through glass or through other transparent media. So here we
have light reflecting off the water, and you can see it
underneath and above. In this next picture, you can see beams
of light, and you can see the caustics on the ground under
water. And this is a little clip from the Justice demo, which
shows how these caustics are underneath the bridge and how
they really sort of bring that area to life, gives it a real
vibrancy. Now, as far as the danger of caustics, it's a real
life danger. So this is a picture of my office, and on my
window sill. Like a lot of computer graphics, people have
little chaskas of different cool materials and things I can stare
at. One of them was this little crystal ball on a wooden
platform. And if you zoom in on that crystal ball, you'll see,
oh, gee, there's there's funny little marks on the wooden
platform. And I hadn't realized this for quite a while. I was
once in one office, then I moved to another office, and you can
see the effect. There are these burn marks in two different
areas, and it just depended on which way the ball was facing.
And luckily, I did not burn down our office. That would not have
been so good. But anyway, this is actually a real problem, like
people will if you Google it, you'll find someone has their
house can light on fire due to snow globes. So beware of
caustics. So I like to keep my caustics virtual. Like to keep
them in the computer graphics world. And so these are just two
shots from the physical based renderer by Matt fire and
others. And it gives these gorgeous effects of light
refracting through these various glass and so on surfaces, and
that's it. For further resources, see the link for all
kinds of free books and whatnot. And one free book in particular,
I'd like to point out is ray tracing. J
Hi. My name is Eric Haynes with Nvidia, and this talk is about
the rendering equation. I'd like to start with a quote from Roman
pain the Muse is not an artistic mystery, but a mathematical
equation. And this is really good for the rendering equation,
the rendering equation, it's not a rendering equation, it's the
rendering equation. It really sums up how light gets to the
eye. And I can already see your eyes drooping, in fact, because
you've just seen an equation put on a slide. Oh my gosh. What are
we doing? This is, if you're going to have one equation in
your life, make it this one. If you're in two computer graphics
it has a few terms in it. It all looks a bit like much, but we'll
break it down in this lesson, and you'll find it's really
worthwhile. It gives you this tool where you can think about
how light works, what effects you want to do, what effects you
want to leave behind. So to start with, there's a bunch of
inputs for the rendering equation, which is there's a
point x, which is some point in the scene, and that's the point.
Let's say that you're looking at and there's an outgoing
direction, which is this omega hat, that W looking thing, omega
hat out o, sub o, and that's an outgoing direction. So it's
basically a direction, say, towards the I. There's also an
incoming direction, which if you look at the far right of the
equation, you see an omega hat I, and that's just some light is
coming in from some other direction. There's this surface
normal, if you have a flat surface, say the floor, the
normal is the direction pointing straight up, for example. And
then finally, there's this S squared term, which means it's
all incoming directions. So we're going to be evaluating
this piece on the right for all incoming directions. Light is
coming from a bunch of different directions. How do they affect
what we finally see from our eye? The terms in this equation,
the first two, are really easy. The outgoing light on the far
left, that's basically saying given a point and giving an
outgoing direction. What light do I see? In other words, I'm
looking in a direction at some point. Well, what light is
coming from that point? To start with, there's the emitted light,
which is a function that looks just about the same. It
basically says, given a point and given an outgoing direction,
what light is coming from that point? So if you have a light
source, a lot of light is coming out from there, and that just
shines right into your eye. And if everything in the world was a
light source, then we'd be good. We wouldn't have to think about
any of the equation to the right where the right equation comes
in. It has an incoming light, a material, and this Lambert
geometric term. So the incoming light is basically saying, OK,
given a point and given some direction, what do I see in that
direction? What light is coming from that direction? The
material equation is just simply a function that says, OK, given
an incoming and an outgoing direction, what light goes in
the outgoing direction? So in other words, like a mirror, for
example, will be very reflective in one direction. So the
incoming and the outgoing directions are closely related,
but other surfaces, many different incoming directions
will give a different term, different amount of light
bouncing off the surface. And then finally, there's this
Lambert term, which is this incoming direction times the
normal and that's a geometric term, and I'll show what that
means. What happens with the Lambert cosine law. It's an old
idea, and it's just simply something that's kind of
intuitively true, that if a light's directly overhead, it's
going to have the most effect on the surface. But as you tilt the
light, the effect of that light is going to be less and less as
it gets to the horizon. So on the far right of this you can
see how the light kind of spreads out as we get to this
shallower angle. And that's all that term is. And this is just
another visualization of that term, where it's showing how it
decreases over angle. So what pure path tracing does is it
basically says, all I'm going to do is I'm going to sum up the
light in all directions, and that's what's going to go
towards the eye. So in path tracing, what we do is we kind
of shoot a ray and then we shoot another ray off that surface in
some other direction. So with path tracing, what we did is
shoot a ray from the eye and hits this box, and then from
there, it scatters out rays in various directions. So each path
is a different direction. One may go up and hit the sky,
another one may go and hit the ground, and that bounces
somewhere else, and so on and so forth. And we add up all the
contributions of those paths to get the color at the EI. The
trick with this is that we don't really know in a given direction
what the light is. Sometimes we do if we look directly at the
sun, well, we know what that is, but often we'll hit something
else. And so the rendering equation is actually a recursive
equation. It's one where it says, well, what's the incoming
light direction and intensity? Rather from a direction? Well,
we don't know. So what we have to do is use the rendering
equation again on the place that we just hit. So if I hit the box
and then I hit the cylinder, we'd apply the rendering
equation at the cylinder and so on and so forth until we finally
get an answer. The trick with that is that if you did a pure
path trace, it's a very slow process to converge if you don't
have a big light source, like, so if you didn't have, for
example, the sky, so that you know when a ray hits the sky,
you're done. You could be in trouble, like if you just have a
small light source in the scene. Pure path tracing says, Well,
I'm going to bounce my rays around until I hit a light. And
that's a problem, because if the light's small, that could be a
very, very long number of bounces. There's things. What we
do about this one is called important sampling, and it
basically says there's got to be good directions for me to go
shoot my rays in. Let's see what they are. One approach with
important sampling is to just look at the effect of the
material. So we take that Lambert term, and we take the
material function, where it has an incoming and an outgoing
direction, which, if you want to impress people at cocktail
parties, is the bi directional scattering distribution
function, the BSDF. And all that is, is a fancy way of saying,
well, when light comes in from this direction, what effect does
it have on the material? For example, if the material is
black, well, there's not going to be any outgoing light, but in
general, there's some outgoing term that will respond to
different directions. With a mirror, for example, it's clear
that the outgoing direction is going to basically be a
reflection direction from the incoming direction, and that's
the only direction that really matters to us. So if we're path
tracing and we hit a perfect mirror, we can just always shoot
our ray out in that direction and feel good about life,
because we know that light from different directions, that it's
not going to really matter too much for a glossy surface where
it's got like a sheen, then you might shoot out a burst of rays.
So for each path, you might choose a different Ray and
decide to go one way or the other and so on. And then adding
up all those paths should give you a pretty good result.
Finally, you have something like a diffuse or a matte surface,
like unglazed pottery or cement or things like that, where light
can be coming in from all different directions and
contribute to the outgoing direction. And there you're
doing more of like a Lambert's law, kind of a distribution
going in all different directions however you want.
Again, that can be expensive. So there's yet another way that we
go to try to reduce the load. It's called multiple important
sampling. And here we say, well, OK, we will vary by the
material, but we also want to vary using the light direction.
So if we know that there's an important light source in the
room, or if they know that there's the suns out there, or
something like that, we'll also add that in as an important
place to shoot rays, basically. So instead of just shooting them
kind of randomly, we'll say, Oh, I also shoot some rays towards
that light, because I know that light's going to be a really
important direct lighting effect. But it's also worthwhile
to shoot these other rays because we want to catch some of
the indirect lighting. So in a mirror reflection or a glossy or
diffuse, it's all sort of the same idea. We're going to try to
shoot a bunch at the light, and we might weight them by how much
they'll matter, that the diffuse one, it's going to matter
perhaps more. The reflection one, perhaps less, because we
really mostly care about what's in the reflection direction. So
I will not go through this image, but it's really worth
looking at. This image of multiple important sampling.
It's from a classic paper 1995 and you can try to think this
one through. Consider this, your quiz is, shininess is varying.
At the top, there are a bunch of light sources, and the radius of
those light sources is increasing in each one of the
three figures. And in one, we're just sampling the light source,
and another, we're sampling this BRDF, which is the bi
directional reflectance distribution function, and
that's like the scattering function, but it's meant for
surfaces, and it's for things that are opaque, not like glass.
And then you have this mis multiple important sampling
where you're doing both, and you can see that both is better,
basically. And this is a good one to try to think through. Why
do some of these images look fuzzy? Once you understand that,
then you've got a level of enlightenment on the rendering
equation. So as an example of path tracing, Nvidia picked up
some open source code from some researchers who were looking at
quick two an old game, but they decided, well, now that we have
ray tracing acceleration, let's do a path trace version of it,
like really crank up the good lighting and materials and so
on. And it makes a dramatic difference. It's the same
assets, but just improving the lighting alone can really make
the game shine, literally. And now you've got the rendering
equation of your build. It's really, honestly a wonderful
tool for thinking about lighting and how it percolates through a
scene and what you care about for further resources. See the
website, and I also want to mention that there's this book
called ray tracing gems that's downloadable for free. You
Hi, I'm Eric Hayne for Nvidia, and this talk is about de
noising for ray tracing. I have a quote today from Daphne
Culler, a Sanford professor of works on AI for biomedical
applications. She says, The world is noisy and messy. You
need to deal with the noise and uncertainty. This is
particularly good for ray tracing, because ray tracing can
be extremely noisy. On the left, you'll see an image that has
five samples per pixel using path tracing, and you can see
it's quite noisy. There's a lot of black pixels that where light
just didn't get anywhere near where we needed it to. After 50
samples, it's starting to look better. 500 better yet, 5000 is
looking pretty darn good. And if you looked at really closely,
you'd still see some noise in there. And in fact, films
themselves have this trouble where they'll shoot 3000 rays
per pixel, but they'll still see some noise. So what they'll use,
and what we're going to use today, is a process called de
noising to make those images better. And you can see there's
a diminishing return here. It's pretty much the variance goes
down with the square root of the number of samples. So if you go
from, say, four samples, that's twice as good as just one
sample, nine samples, that's three times as good as one
sample. But it's diminishing returns. So we just can't afford
to shoot 5000 rays per pixel right now, so we have to do
something else. And as they say, That's de noising. Our reality
is that we start with a noisy image if we're doing any kind of
more elaborate effects, and we have to try to get to a nicer
image. We'd love to get this kind of image, but we often will
have a crude, noisy image, and then we have to reconstruct. So
reconstruction is called de noising, and there are various
ways to do it. Here's another example, where the left is noisy
and the right is de noised. This de noising process can be
extremely fast. It says identical time, but it's almost
identical time. It's the blink of an eye. And what de noising
does is basically look at that area at the various surfaces,
and tries to use data, both in color channel and any other kind
of information they might want to use, like the normal or the
color of the texture that's underlying the surface. And use
that to come up with some kind of filtering process where it
tries to fill in, tries to infer what's going on in the surface,
so you could denoise by effect, for example. So in this image,
we have a nice, soft shadow given by that plant onto a
floor. But it might be difficult to actually de noise this if you
try to do it on the final image, because the floor of rain would
possibly mess up your algorithm. So what you could do is instead
de noise just the shadow image, which would just be a bunch of
gray scale tones, and then you would fold that in with the
textured surface and get a nice final effect. The problem with
denoising by effect is that if you did this for every single
pass, it would start to really add up. The de noising cost
would become exorbitant. So what we try to do is de noise on the
final image that we would have just one denoising pass. So on
the left we have the original image, and on the right we have
a human filtered image and a neural network filtered image.
And the human one is basically using sort of traditional
denoising techniques and then tweaking and so on, and the
neural network is using an entirely different process.
What's interesting here is that I think the computers are
winning, because in the upper right, you can kind of see that
back wall, there's a little strip of green. It's kind of
blurred out a little bit too much with the human version, but
the neural network has picked up on that and kept the vertical
stripes there. Deep learning can be used for image denoising. The
way this works is that we have a bunch of rendered images, 20,000
40,000 however many we can get as training data, and then we
train our neural net using those images to have the neural net
kind of know what the environment is like. We can then
use that neural net to take a noisy image and have it infer
what the real image should look like. So we have some huge
training set, or some reasonable training set. It just depends.
And from that, we then can actually do a great job of de
noising images, surprisingly good. So here's a noisy image,
one sample per pixel, and here's our de noise image. So the
shadows look really nice, and notice how soft they are. A
little bit of soft shadow. It's a fairly nice final dimension.
You can compare that to the ground truth. They're almost
identical. In comparison, the traditional method in
rasterization is to use shadow mapping, where you render
everything from the lights point of view. Here you get somewhat
sharper kinds of shadows. They're just not as beautiful,
let's face it, and it has other kinds of problems, like that.
One person is floating a little bit. It's called Peter panning,
and this can be avoided by using newer techniques. Here's another
example of denoising, where we have this shiny surface varying
in roughness and de noised. It looks pretty good. And here's
the ground truth. Now, there's a fair bit of difference between
the de noised and the ground truth here, but it's enough to
be plausible. It's a reasonable result, and it's one that is
going to basically be reasonable to most people's visual systems.
They're not going to be surprised or shocked by the
result. In comparison, here's one that's pretty different,
actually. This is called stochastic screen space
reflection method that uses rasterization, and it's kind of
using information in the screen, and it has problems. There are
ways that it works fairly well, but there's other places where
it kind of falls apart. To show you the comparison, again, we
have the ground truth and the spring space reflection, and you
can see they're considerably different. Here's another image.
Here we have just one sample per pixel of Ray Traced global
illumination and de noising, we get this really pretty fantastic
result. It just blows me away that it can do this well. To
compare this to ground truth, in the ground truth image, you'll
notice a little bit of darkening around the fringes of things and
in the crevices and so on. But for the most part, the images
are quite comparable. Last I'm going to finish off with an
animation. So there's a movie that was rendered called zero
day by this person called people, and he kindly put his
entire database and animation path and so on on the web for
people to reuse as they will. So we use this at Nvidia to
experiment with different denoising operations. This is a
pretty complicated scene. There's actually about more than
7000 individual triangles that are moving around that are
lights. So those light sources are all moving around. And
moving light sources can be quite tricky to capture nicely.
And so in this video, what you're seeing is, on the left,
you're seeing four samples per pixel and about 16 raised shot
per pixel total. They're bouncing around a bit, and the
de noised is on the right now. This is not real time at this
point. It's about seven frames per second. It's the calculation
going on here. But you can see that this noise result is quite
nice. Here's the final result using denoising, and if you
want, you can compare it to the original. There will be links on
the website. It looks quite nice. You have to really kind of
freeze frame and do a side by side to see where there are
slight differences between this and the one where they traced
1000s of rays per pixel. De noising, to me, is magic. To
summarize, it's just this cool technique that can work
surprisingly well. I'm cleaning up a lot of problems and a lot
of under sampling that we'd love to have more samples, but we
can't. And I think, to me, it's what really made ray tracing
jump ahead a little bit more quickly than people expected. I
think we all sort of thinking, Well, Ray tracing eventually
there will be hardware, but de noising really takes a great
leap. You know, instead of needing 1000s of samples or
hundreds of samples, or even 10s of samples, we can get by with
just a few samples in many, many situations. To conclude, I'd
like to have one more quote. So we started this whole series
with There's an old joke that goes, Ray tracing is the
technology of the future and always will be. Well, the future
is here. And I like this quote from Steve Parker, which is, Ray
tracing is simple enough to fit on a business card, yet
complicated enough to consume an entire career. Prefer the
resources see the website, Ray tracing gems is a book I highly
recommend, given that I co edited, and it's free for
download, and I hope you take advantage of it, and thanks for
letting me have your time. You
what'd you think do? Yes, actually, it's related
my thesis in the
course of the deep learning I thought I mean Ambient Occlusion
was pretty cool. Anybody was never in yet. How can we do the
de noise thing in pbrt? Because often we get out of gamut
pixels. Can we? Can we reduce that using like denoising?
I'm not
my parent Sure, yeah,
I'm not sure if that needs a GPU.
I will investigate. I'm
thinking, Oh, that would be like a perfect, like solution to our
out of gap pixels. Is the de noise out
there? Yes. And did the crown look familiar?
That was the test image that we looked at early On this
semester. It's
I so I just want to Touch on our quiz for today. Thank
you. So what is a convenient bounding volume for shapes? For
for some reason that sentence sounds really weird to my ears.
What is a convenient bounding like, sorry.
Okay, I'll accept that it's maybe a bit of tension between
singular and plural.
So it was in the videos that it
was
like objects that, like emit light, like it was trying to
remember exactly what I read.
So it's not about emitting it's
so we talked first about circles and spheres bounding objects in
the scene. Then he said, but in ray tracing, we Use boxes and
more particularly, access aligned boxes. Oh,
so how are area lights defined in pbrt? Do?
Does
it? Doesn't it? Like, use, like the normals of like, the shape
to project lines. Is that right?
Oh, we want to attach an emit.
Attach An emitter. We
attach an emission profile and
so we're going to attach that profile to a square,
or whatever we want to
have be the area light we're
and then, why is it useful to have bounds for normals? Why are
normal bounds specifically useful in rendering? Do
maybe I just misunderstood what I meant by when a shape is
emissive. But it's useful for for that, and that's is that
when you're having like, a like, an actual shape for your light
source, like, because normally, lights come from a point, often,
is what we do. So if you have like, let's say, a balloon that
was emitting light, that would be an emissive balloon. Is that
correct? Like you're emitting light from a shape, as opposed
to a point, and that's why it's that's why it's useful the
normal bounds.
So we can think of like a cone that contains the bound it
balances the light using its shape and
so if we have a bound for So, a similar thing is, if we have a
spotlight, then we're shooting
in the cone. And if we can bound the normals in a similar way,
that helps us to determine what's visible
and efficient. I
I'll review the answers you gave.
So It's basically for illumination.
I'm late here.
From the text, it's normal boundary, specifically useful in
lighting time patients, when a shape is emissive, they
sometimes make it possible. This sometimes makes it possible to
officially determine that the shape does not eliminate a
bigger point in the scene.
Yeah. So
So it's more of a bound. It limits it. It's like saying a
light a light fixture, points the light downward, and then it
doesn't need to calculate to the right and to the left of that
light. Is that sort of
apt. We'll talk about it next day.
And also you
can think about
how to make that desktop tetrahedron. We'll
talk about that as well. Okay,
the pyramid that one,
it's not a pyramid. Pyramid has four sides. Oh,
three sides. Okay, yeah, I think I did program it
already. Okay. Anyway, thank you for today.
See you on Thursday. I.

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