5 ms·

Ahhh, the 2nd rendering bible, together with Eric Veach's thesis: https://graphics.stanford.edu/papers/veach_thesis/ https://graphics.stanford.edu/papers/veach_

Ahhh, the 2nd rendering bible, together with Eric Veach's thesis: https://graphics.stanford.edu/papers/veach_thesis/ https://graphics.stanford.edu/papers/veach_thesis/ I've spent my entire life studying this stuff and feel extremely lucky on so many levels: that we have these incredible computers which can actually do the computation, that we happen to have such a powerful theory that can model and even predict visual reality, and perhaps most of all, that a single person can learn all this stuff and carry it around with them everyday - it's really changed how I see the world. My deepest thanks go to those who have developed and passed all this on through their papers and books; it's literally what I'm getting the meaning of life from.

blenderdt 5y ago
What I also think is amazing is that algorithms improve all the time. For example the Blender Cycles render engine has been rewritten lately. Using the latest knowlegde and algorithms it is now more than twice as fast.
- pixelpoet 5y ago
  Yep, and that design had been presented ages ago[0] already by the Finnish geniuses who basically designed Nvidia's ray tracing tech[1] (as well as the state of the art in GANs[2]), and even implemented in some lesser-known renderers like Indigo Renderer :) These days the most exciting research I think is in path guiding and many-light sampling techniques. [0] https://research.nvidia.com/sites/default/files/pubs/2013-07_Megakernels-Considered-Harmful/laine2013hpg_paper.pdf https://research.nvidia.com/sites/default/files/pubs/2013-07... [1] https://research.nvidia.com/publication/understanding-efficiency-ray-traversal-gpus https://research.nvidia.com/publication/understanding-effici... [2] https://research.nvidia.com/publication/2021-06_Alias-Free-GAN https://research.nvidia.com/publication/2021-06_Alias-Free-G...
- ur-whale 5y ago
  Yeah, except that Cycles focus isn't on accurate physical rendering, but rather on quick and dirty, visually pleasing approximations. Its primary purpose is to be be used by artists for SFX type work, but if you're looking to make really accurate renderings of complex lighting scenes, for e.g. accurate architectural renderings, I would not use cycles and look at luxcore [0][1] instead. [0] https://luxcorerender.org/ https://luxcorerender.org/ [1] https://github.com/LuxCoreRender https://github.com/LuxCoreRender
nomel 5y ago
Tickling your passion a bit, what's your favorite concept, or bit of math, in this context?
- pixelpoet 5y ago
  I would say very close to the top is the amazing depth of sampling methods, in particular Quasi-Monte Carlo (QMC) methods. I'll try to give a small sample of that. Basically what you're doing in MC is estimating expected values (and thereby integrals: average height times base width equals area under the graph) using random numbers, to be roughly thought of as a rnd() function which gives you back a float in [0,1). However, using actual proper random number generators has a very slow convergence rate, as the random numbers chosen will tend to clump; on the other hand, if you just use a perfectly uniform distribution, you'll suffer from correlation problems. Consider a 1-D numerical integration problem, and instead of using rnd() to pick points in your integrand range, you start with some seed value in [0,1), and each time you need a new random number, you add phi-1 to the existing number and mod with 1.0 to get the new number. If you plot this sequence on a [0,1) number line, you'll see that it divides up the interval into finer pieces really nicely, magically keeping a good distance from all the previous values, without even knowing them! Why does this work? Well, there's a lot of beautiful theory about phi (also relating to biology and nature, e.g. seashells and the distribution of sunflower seeds), in particular how it is in some sense (continued fraction) the "most irrational" number. Does it work well for other numbers, and can it be extended to higher dimensions? Sure, there are some interesting things you can do: http://extremelearning.com.au/unreasonable-effectiveness-of-quasirandom-sequences/ http://extremelearning.com.au/unreasonable-effectiveness-of-... This isn't even scratching the surface of things like the Halton, Hammersley and Sobol sequences, the human visual response to different kinds of noise that makes blue noise preferable, etc. Here's a wealth of recent research on all that: https://sites.google.com/view/myfavoritesamples https://sites.google.com/view/myfavoritesamples Rendering is particularly beautiful in that it touches on so many fields, from pure maths, to applied maths and numerical methods, to physics, to human biology and perception, aesthetics, both low- and high-level programming concerns, even philosophy: if we can simulate visual reality to such high precision, it lends credence to the idea that we ourselves are simulated. To me the apparently obvious truth of this is up there with understanding that the iron that makes our blood red can only be formed in supernovae.
franzb 5y ago
Hey, any way to contact you? Didn’t see an email in your profile. Mine is in my profile (franz@appleseedhq.net).
- pixelpoet 5y ago
  I'll ping you on Discord, we kinda know each other :) Also thanks, forgot to fill that out. For others who like opensource renderers: Appleseed (which Franz is lead developer of) is amazing, check it out! https://appleseedhq.net/ https://appleseedhq.net/
RandomBK 5y ago
That 432-page textbook was a PhD Dissertation? Wow... I'm assuming this is not typical for most PhD theses?
- ur-whale 5y ago
  Veach is in no way a "typical" person. IIRC, he moved on from inventing a brand new rendering methodology inspired from oldie research in nuclear physics [0] to designing the S2 system at Google [1] to building one of the largest money-making machines in the ads world at Google [2][3]. Not exactly your average engineer. [0] https://en.wikipedia.org/wiki/Nicholas_Metropolis https://en.wikipedia.org/wiki/Nicholas_Metropolis [1] https://en.wikipedia.org/wiki/Eric_Veach https://en.wikipedia.org/wiki/Eric_Veach [2] https://uwaterloo.ca/math/people-profiles/eric-veach https://uwaterloo.ca/math/people-profiles/eric-veach [3] https://www.businessinsider.com/unsung-google-heros-2011-5?r=US&IR=T#eric-veach-was-key-in-building-adwords-for-google-8 https://www.businessinsider.com/unsung-google-heros-2011-5?r...
  - deleted 5y ago
    [deleted]

blenderdt 5y ago

What I also think is amazing is that algorithms improve all the time. For example the Blender Cycles render engine has been rewritten lately. Using the latest knowlegde and algorithms it is now more than twice as fast.

pixelpoet 5y ago
Yep, and that design had been presented ages ago[0] already by the Finnish geniuses who basically designed Nvidia's ray tracing tech[1] (as well as the state of the art in GANs[2]), and even implemented in some lesser-known renderers like Indigo Renderer :) These days the most exciting research I think is in path guiding and many-light sampling techniques. [0] https://research.nvidia.com/sites/default/files/pubs/2013-07_Megakernels-Considered-Harmful/laine2013hpg_paper.pdf https://research.nvidia.com/sites/default/files/pubs/2013-07... [1] https://research.nvidia.com/publication/understanding-efficiency-ray-traversal-gpus https://research.nvidia.com/publication/understanding-effici... [2] https://research.nvidia.com/publication/2021-06_Alias-Free-GAN https://research.nvidia.com/publication/2021-06_Alias-Free-G...
ur-whale 5y ago
Yeah, except that Cycles focus isn't on accurate physical rendering, but rather on quick and dirty, visually pleasing approximations. Its primary purpose is to be be used by artists for SFX type work, but if you're looking to make really accurate renderings of complex lighting scenes, for e.g. accurate architectural renderings, I would not use cycles and look at luxcore [0][1] instead. [0] https://luxcorerender.org/ https://luxcorerender.org/ [1] https://github.com/LuxCoreRender https://github.com/LuxCoreRender

nomel 5y ago

Tickling your passion a bit, what's your favorite concept, or bit of math, in this context?

pixelpoet 5y ago
I would say very close to the top is the amazing depth of sampling methods, in particular Quasi-Monte Carlo (QMC) methods. I'll try to give a small sample of that. Basically what you're doing in MC is estimating expected values (and thereby integrals: average height times base width equals area under the graph) using random numbers, to be roughly thought of as a rnd() function which gives you back a float in [0,1). However, using actual proper random number generators has a very slow convergence rate, as the random numbers chosen will tend to clump; on the other hand, if you just use a perfectly uniform distribution, you'll suffer from correlation problems. Consider a 1-D numerical integration problem, and instead of using rnd() to pick points in your integrand range, you start with some seed value in [0,1), and each time you need a new random number, you add phi-1 to the existing number and mod with 1.0 to get the new number. If you plot this sequence on a [0,1) number line, you'll see that it divides up the interval into finer pieces really nicely, magically keeping a good distance from all the previous values, without even knowing them! Why does this work? Well, there's a lot of beautiful theory about phi (also relating to biology and nature, e.g. seashells and the distribution of sunflower seeds), in particular how it is in some sense (continued fraction) the "most irrational" number. Does it work well for other numbers, and can it be extended to higher dimensions? Sure, there are some interesting things you can do: http://extremelearning.com.au/unreasonable-effectiveness-of-quasirandom-sequences/ http://extremelearning.com.au/unreasonable-effectiveness-of-... This isn't even scratching the surface of things like the Halton, Hammersley and Sobol sequences, the human visual response to different kinds of noise that makes blue noise preferable, etc. Here's a wealth of recent research on all that: https://sites.google.com/view/myfavoritesamples https://sites.google.com/view/myfavoritesamples Rendering is particularly beautiful in that it touches on so many fields, from pure maths, to applied maths and numerical methods, to physics, to human biology and perception, aesthetics, both low- and high-level programming concerns, even philosophy: if we can simulate visual reality to such high precision, it lends credence to the idea that we ourselves are simulated. To me the apparently obvious truth of this is up there with understanding that the iron that makes our blood red can only be formed in supernovae.

franzb 5y ago

Hey, any way to contact you? Didn’t see an email in your profile. Mine is in my profile (franz@appleseedhq.net).

pixelpoet 5y ago
I'll ping you on Discord, we kinda know each other :) Also thanks, forgot to fill that out. For others who like opensource renderers: Appleseed (which Franz is lead developer of) is amazing, check it out! https://appleseedhq.net/ https://appleseedhq.net/

RandomBK 5y ago

That 432-page textbook was a PhD Dissertation? Wow... I'm assuming this is not typical for most PhD theses?

ur-whale 5y ago
Veach is in no way a "typical" person. IIRC, he moved on from inventing a brand new rendering methodology inspired from oldie research in nuclear physics [0] to designing the S2 system at Google [1] to building one of the largest money-making machines in the ads world at Google [2][3]. Not exactly your average engineer. [0] https://en.wikipedia.org/wiki/Nicholas_Metropolis https://en.wikipedia.org/wiki/Nicholas_Metropolis [1] https://en.wikipedia.org/wiki/Eric_Veach https://en.wikipedia.org/wiki/Eric_Veach [2] https://uwaterloo.ca/math/people-profiles/eric-veach https://uwaterloo.ca/math/people-profiles/eric-veach [3] https://www.businessinsider.com/unsung-google-heros-2011-5?r=US&IR=T#eric-veach-was-key-in-building-adwords-for-google-8 https://www.businessinsider.com/unsung-google-heros-2011-5?r...
- deleted 5y ago
  [deleted]