COMPOSITION
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Composition – 5 tips for creating perfect cinematic lighting and making your work look stunning
Read more: Composition – 5 tips for creating perfect cinematic lighting and making your work look stunning
http://www.diyphotography.net/5-tips-creating-perfect-cinematic-lighting-making-work-look-stunning/
1. Learn the rules of lighting
2. Learn when to break the rules
3. Make your key light larger
4. Reverse keying
5. Always be backlighting
DESIGN
COLOR
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HDR and Color
Read more: HDR and Colorhttps://www.soundandvision.com/content/nits-and-bits-hdr-and-color
In HD we often refer to the range of available colors as a color gamut. Such a color gamut is typically plotted on a two-dimensional diagram, called a CIE chart, as shown in at the top of this blog. Each color is characterized by its x/y coordinates.
Good enough for government work, perhaps. But for HDR, with its higher luminance levels and wider color, the gamut becomes three-dimensional.
For HDR the color gamut therefore becomes a characteristic we now call the color volume. It isn’t easy to show color volume on a two-dimensional medium like the printed page or a computer screen, but one method is shown below. As the luminance becomes higher, the picture eventually turns to white. As it becomes darker, it fades to black. The traditional color gamut shown on the CIE chart is simply a slice through this color volume at a selected luminance level, such as 50%.
Three different color volumes—we still refer to them as color gamuts though their third dimension is important—are currently the most significant. The first is BT.709 (sometimes referred to as Rec.709), the color gamut used for pre-UHD/HDR formats, including standard HD.
The largest is known as BT.2020; it encompasses (roughly) the range of colors visible to the human eye (though ET might find it insufficient!).
Between these two is the color gamut used in digital cinema, known as DCI-P3.
sRGB
D65
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Mysterious animation wins best illusion of 2011 – Motion silencing illusion
Read more: Mysterious animation wins best illusion of 2011 – Motion silencing illusionThe 2011 Best Illusion of the Year uses motion to render color changes invisible, and so reveals a quirk in our visual systems that is new to scientists.
https://en.wikipedia.org/wiki/Motion_silencing_illusion
“It is a really beautiful effect, revealing something about how our visual system works that we didn’t know before,” said Daniel Simons, a professor at the University of Illinois, Champaign-Urbana. Simons studies visual cognition, and did not work on this illusion. Before its creation, scientists didn’t know that motion had this effect on perception, Simons said.
A viewer stares at a speck at the center of a ring of colored dots, which continuously change color. When the ring begins to rotate around the speck, the color changes appear to stop. But this is an illusion. For some reason, the motion causes our visual system to ignore the color changes. (You can, however, see the color changes if you follow the rotating circles with your eyes.)
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Image rendering bit depth
Read more: Image rendering bit depthThe terms 8-bit, 16-bit, 16-bit float, and 32-bit refer to different data formats used to store and represent image information, as bits per pixel.
https://en.wikipedia.org/wiki/Color_depth
In color technology, color depth also known as bit depth, is either the number of bits used to indicate the color of a single pixel, OR the number of bits used for each color component of a single pixel.
When referring to a pixel, the concept can be defined as bits per pixel (bpp).
When referring to a color component, the concept can be defined as bits per component, bits per channel, bits per color (all three abbreviated bpc), and also bits per pixel component, bits per color channel or bits per sample (bps). Modern standards tend to use bits per component, but historical lower-depth systems used bits per pixel more often.
Color depth is only one aspect of color representation, expressing the precision with which the amount of each primary can be expressed; the other aspect is how broad a range of colors can be expressed (the gamut). The definition of both color precision and gamut is accomplished with a color encoding specification which assigns a digital code value to a location in a color space.
Here’s a simple explanation of each.
8-bit images (i.e. 24 bits per pixel for a color image) are considered Low Dynamic Range.
They can store around 5 stops of light and each pixel carry a value from 0 (black) to 255 (white).
As a comparison, DSLR cameras can capture ~12-15 stops of light and they use RAW files to store the information.16-bit: This format is commonly referred to as “half-precision.” It uses 16 bits of data to represent color values for each pixel. With 16 bits, you can have 65,536 discrete levels of color, allowing for relatively high precision and smooth gradients. However, it has a limited dynamic range, meaning it cannot accurately represent extremely bright or dark values. It is commonly used for regular images and textures.
16-bit float: This format is an extension of the 16-bit format but uses floating-point numbers instead of fixed integers. Floating-point numbers allow for more precise calculations and a larger dynamic range. In this case, the 16 bits are used to store both the color value and the exponent, which controls the range of values that can be represented. The 16-bit float format provides better accuracy and a wider dynamic range than regular 16-bit, making it useful for high-dynamic-range imaging (HDRI) and computations that require more precision.
32-bit: (i.e. 96 bits per pixel for a color image) are considered High Dynamic Range. This format, also known as “full-precision” or “float,” uses 32 bits to represent color values and offers the highest precision and dynamic range among the three options. With 32 bits, you have a significantly larger number of discrete levels, allowing for extremely accurate color representation, smooth gradients, and a wide range of brightness values. It is commonly used for professional rendering, visual effects, and scientific applications where maximum precision is required.
Bits and HDR coverage
High Dynamic Range (HDR) images are designed to capture a wide range of luminance values, from the darkest shadows to the brightest highlights, in order to reproduce a scene with more accuracy and detail. The bit depth of an image refers to the number of bits used to represent each pixel’s color information. When comparing 32-bit float and 16-bit float HDR images, the drop in accuracy primarily relates to the precision of the color information.
A 32-bit float HDR image offers a higher level of precision compared to a 16-bit float HDR image. In a 32-bit float format, each color channel (red, green, and blue) is represented by 32 bits, allowing for a larger range of values to be stored. This increased precision enables the image to retain more details and subtleties in color and luminance.
On the other hand, a 16-bit float HDR image utilizes 16 bits per color channel, resulting in a reduced range of values that can be represented. This lower precision leads to a loss of fine details and color nuances, especially in highly contrasted areas of the image where there are significant differences in luminance.
The drop in accuracy between 32-bit and 16-bit float HDR images becomes more noticeable as the exposure range of the scene increases. Exposure range refers to the span between the darkest and brightest areas of an image. In scenes with a limited exposure range, where the luminance differences are relatively small, the loss of accuracy may not be as prominent or perceptible. These images usually are around 8-10 exposure levels.
However, in scenes with a wide exposure range, such as a landscape with deep shadows and bright highlights, the reduced precision of a 16-bit float HDR image can result in visible artifacts like color banding, posterization, and loss of detail in both shadows and highlights. The image may exhibit abrupt transitions between tones or colors, which can appear unnatural and less realistic.
To provide a rough estimate, it is often observed that exposure values beyond approximately ±6 to ±8 stops from the middle gray (18% reflectance) may be more prone to accuracy issues in a 16-bit float format. This range may vary depending on the specific implementation and encoding scheme used.
To summarize, the drop in accuracy between 32-bit and 16-bit float HDR images is mainly related to the reduced precision of color information. This decrease in precision becomes more apparent in scenes with a wide exposure range, affecting the representation of fine details and leading to visible artifacts in the image.
In practice, this means that exposure values beyond a certain range will experience a loss of accuracy and detail when stored in a 16-bit float format. The exact range at which this loss occurs depends on the encoding scheme and the specific implementation. However, in general, extremely bright or extremely dark values that fall outside the representable range may be subject to quantization errors, resulting in loss of detail, banding, or other artifacts.
HDRs used for lighting purposes are usually slightly convolved to improve on sampling speed and removing specular artefacts. To that extent, 16 bit float HDRIs tend to me most used in CG cycles.
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Tim Kang – calibrated white light values in sRGB color space
Read more: Tim Kang – calibrated white light values in sRGB color space8bit sRGB encoded
2000K 255 139 22
2700K 255 172 89
3000K 255 184 109
3200K 255 190 122
4000K 255 211 165
4300K 255 219 178
D50 255 235 205
D55 255 243 224
D5600 255 244 227
D6000 255 249 240
D65 255 255 255
D10000 202 221 255
D20000 166 196 2558bit Rec709 Gamma 2.4
2000K 255 145 34
2700K 255 177 97
3000K 255 187 117
3200K 255 193 129
4000K 255 214 170
4300K 255 221 182
D50 255 236 208
D55 255 243 226
D5600 255 245 229
D6000 255 250 241
D65 255 255 255
D10000 204 222 255
D20000 170 199 2558bit Display P3 encoded
2000K 255 154 63
2700K 255 185 109
3000K 255 195 127
3200K 255 201 138
4000K 255 219 176
4300K 255 225 187
D50 255 239 212
D55 255 245 228
D5600 255 246 231
D6000 255 251 242
D65 255 255 255
D10000 208 223 255
D20000 175 199 25510bit Rec2020 PQ (100 nits)
2000K 520 435 273
2700K 520 466 358
3000K 520 475 384
3200K 520 480 399
4000K 520 495 446
4300K 520 500 458
D50 520 510 482
D55 520 514 497
D5600 520 514 500
D6000 520 517 509
D65 520 520 520
D10000 479 489 520
D20000 448 464 520
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Björn Ottosson – OKHSV and OKHSL – Two new color spaces for color picking
Read more: Björn Ottosson – OKHSV and OKHSL – Two new color spaces for color pickinghttps://bottosson.github.io/misc/colorpicker
https://bottosson.github.io/posts/colorpicker/
https://www.smashingmagazine.com/2024/10/interview-bjorn-ottosson-creator-oklab-color-space/
One problem with sRGB is that in a gradient between blue and white, it becomes a bit purple in the middle of the transition. That’s because sRGB really isn’t created to mimic how the eye sees colors; rather, it is based on how CRT monitors work. That means it works with certain frequencies of red, green, and blue, and also the non-linear coding called gamma. It’s a miracle it works as well as it does, but it’s not connected to color perception. When using those tools, you sometimes get surprising results, like purple in the gradient.
There were also attempts to create simple models matching human perception based on XYZ, but as it turned out, it’s not possible to model all color vision that way. Perception of color is incredibly complex and depends, among other things, on whether it is dark or light in the room and the background color it is against. When you look at a photograph, it also depends on what you think the color of the light source is. The dress is a typical example of color vision being very context-dependent. It is almost impossible to model this perfectly.
I based Oklab on two other color spaces, CIECAM16 and IPT. I used the lightness and saturation prediction from CIECAM16, which is a color appearance model, as a target. I actually wanted to use the datasets used to create CIECAM16, but I couldn’t find them.
IPT was designed to have better hue uniformity. In experiments, they asked people to match light and dark colors, saturated and unsaturated colors, which resulted in a dataset for which colors, subjectively, have the same hue. IPT has a few other issues but is the basis for hue in Oklab.
In the Munsell color system, colors are described with three parameters, designed to match the perceived appearance of colors: Hue, Chroma and Value. The parameters are designed to be independent and each have a uniform scale. This results in a color solid with an irregular shape. The parameters are designed to be independent and each have a uniform scale. This results in a color solid with an irregular shape. Modern color spaces and models, such as CIELAB, Cam16 and Björn Ottosson own Oklab, are very similar in their construction.
By far the most used color spaces today for color picking are HSL and HSV, two representations introduced in the classic 1978 paper “Color Spaces for Computer Graphics”. HSL and HSV designed to roughly correlate with perceptual color properties while being very simple and cheap to compute.
Today HSL and HSV are most commonly used together with the sRGB color space.
One of the main advantages of HSL and HSV over the different Lab color spaces is that they map the sRGB gamut to a cylinder. This makes them easy to use since all parameters can be changed independently, without the risk of creating colors outside of the target gamut.
The main drawback on the other hand is that their properties don’t match human perception particularly well.
Reconciling these conflicting goals perfectly isn’t possible, but given that HSV and HSL don’t use anything derived from experiments relating to human perception, creating something that makes a better tradeoff does not seem unreasonable.
With this new lightness estimate, we are ready to look into the construction of Okhsv and Okhsl.
LIGHTING
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Lighting Every Darkness with 3DGS: Fast Training and Real-Time Rendering and Denoising for HDR View Synthesis
Read more: Lighting Every Darkness with 3DGS: Fast Training and Real-Time Rendering and Denoising for HDR View Synthesishttps://srameo.github.io/projects/le3d/
LE3D is a method for real-time HDR view synthesis from RAW images. It is particularly effective for nighttime scenes.
https://github.com/Srameo/LE3D
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Arto T. – A workflow for creating photorealistic, equirectangular 360° panoramas in ComfyUI using Flux
Read more: Arto T. – A workflow for creating photorealistic, equirectangular 360° panoramas in ComfyUI using Fluxhttps://civitai.com/models/735980/flux-equirectangular-360-panorama
https://civitai.com/models/745010?modelVersionId=833115
The trigger phrase is “equirectangular 360 degree panorama”. I would avoid saying “spherical projection” since that tends to result in non-equirectangular spherical images.
Image resolution should always be a 2:1 aspect ratio. 1024 x 512 or 1408 x 704 work quite well and were used in the training data. 2048 x 1024 also works.
I suggest using a weight of 0.5 – 1.5. If you are having issues with the image generating too flat instead of having the necessary spherical distortion, try increasing the weight above 1, though this could negatively impact small details of the image. For Flux guidance, I recommend a value of about 2.5 for realistic scenes.
8-bit output at the moment
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Tracing Spherical harmonics and how Weta used them in production
Read more: Tracing Spherical harmonics and how Weta used them in productionA way to approximate complex lighting in ultra realistic renders.
All SH lighting techniques involve replacing parts of standard lighting equations with spherical functions that have been projected into frequency space using the spherical harmonics as a basis.
http://www.cs.columbia.edu/~cs4162/slides/spherical-harmonic-lighting.pdf
Spherical harmonics as used at Weta Digital
https://www.fxguide.com/fxfeatured/the-science-of-spherical-harmonics-at-weta-digital/
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Ethan Roffler interviews CG Supervisor Daniele Tosti
Read more: Ethan Roffler interviews CG Supervisor Daniele TostiEthan Roffler
I recently had the honor of interviewing this VFX genius and gained great insight into what it takes to work in the entertainment industry. Keep in mind, these questions are coming from an artist’s perspective but can be applied to any creative individual looking for some wisdom from a professional. So grab a drink, sit back, and enjoy this fun and insightful conversation.
Ethan
To start, I just wanted to say thank you so much for taking the time for this interview!Daniele
My pleasure.
When I started my career I struggled to find help. Even people in the industry at the time were not that helpful. Because of that, I decided very early on that I was going to do exactly the opposite. I spend most of my weekends talking or helping students. ;)Ethan
That’s awesome! I have also come across the same struggle! Just a heads up, this will probably be the most informal interview you’ll ever have haha! Okay, so let’s start with a small introduction!Daniele
Short introduction: I worked very hard and got lucky enough to work on great shows with great people. ;) Slightly longer version: I started working for a TV channel, very early, while I was learning about CG. Slowly made my way across the world, working along very great people and amazing shows. I learned that to be successful in this business, you have to really love what you do as much as respecting the people around you. What you do will improve to the final product; the way you work with people will make a difference in your life.
Ethan
How long have you been an artist?Daniele
Loaded question. I believe I am still trying and craving to be one. After each production I finish I realize how much I still do not know. And how many things I would like to try. I guess in my CG Sup and generalist world, being an artist is about learning as much about the latest technologies and production cycles as I can, then putting that in practice. Having said that, I do consider myself a cinematographer first, as I have been doing that for about 25 years now.Ethan
Words of true wisdom, the more I know the less I know:) How did you get your start in the industry?
How did you break into such a competitive field?Daniele
There were not many schools when I started. It was all about a few magazines, some books, and pushing software around trying to learn how to make pretty images. Opportunities opened because of that knowledge! The true break was learning to work hard to achieve a Suspension of Disbelief in my work that people would recognize as such. It’s not something everyone can do, but I was fortunate to not be scared of working hard, being a quick learner and having very good supervisors and colleagues to learn from.Ethan
Which do you think is better, having a solid art degree or a strong portfolio?Daniele
Very good question. A strong portfolio will get you a job now. A solid strong degree will likely get you a job for a longer period. Let me digress here; Working as an artist is not about being an artist, it’s about making money as an artist. Most people fail to make that difference and have either a poor career or lack the understanding to make a stable one. One should never mix art with working as an artist. You can do both only if you understand business and are fair to yourself.
Ethan
That’s probably the most helpful answer to that question I have ever heard.
What’s some advice you can offer to someone just starting out who wants to break into the industry?Daniele
Breaking in the industry is not just about knowing your art. It’s about knowing good business practices. Prepare a good demo reel based on the skill you are applying for; research all the places where you want to apply and why; send as many reels around; follow up each reel with a phone call. Business is all about right time, right place.Ethan
A follow-up question to that is: Would you consider it a bad practice to send your demo reels out in mass quantity rather than focusing on a handful of companies to research and apply for?Daniele
Depends how desperate you are… I would say research is a must. To improve your options, you need to know which company is working on what and what skills they are after. If you were selling vacuum cleaners you probably would not want to waste energy contacting shoemakers or cattle farmers.Ethan
What do you think the biggest killer of creativity and productivity is for you?Daniele
Money…If you were thinking as an artist. ;) If you were thinking about making money as an artist… then I would say “thinking that you work alone”.Ethan
Best. Answer. Ever.
What are ways you fight complacency and maintain fresh ideas, outlooks, and perspectivesDaniele
Two things: Challenge yourself to go outside your comfort zone. And think outside of the box.Ethan
What are the ways/habits you have that challenge yourself to get out of your comfort zone and think outside the box?Daniele
If you think you are a good character painter, pick up a camera and go take pictures of amazing landscapes. If you think you are good only at painting or sketching, learn how to code in python. If you cannot solve a problem, that being a project or a person, learn to ask for help or learn about looking at the problem from various perspectives. If you are introvert, learn to be extrovert. And vice versa. And so on…
Ethan
How do you avoid burnout?Daniele
Oh… I wish I learned about this earlier. I think anyone that has a passion in something is at risk of burning out. Artists, more than many, because we see the world differently and our passion goes deep. You avoid burnouts by thinking that you are in a long term plan and that you have an obligation to pay or repay your talent by supporting and cherishing yourself and your family, not your paycheck. You do this by treating your art as a business and using business skills when dealing with your career and using artistic skills only when you are dealing with a project itself.Ethan
Looking back, what was a big defining moment for you?Daniele
Recognizing that people around you, those being colleagues, friends or family, come first.
It changed my career overnight.Ethan
Who are some of your personal heroes?Daniele
Too many to list. Most recently… James Cameron; Joe Letteri; Lawrence Krauss; Richard Dawkins. Because they all mix science, art, and poetry in their own way.Ethan
Last question:
What’s your dream job? ;)Daniele
Teaching artists to be better at being business people… as it will help us all improve our lives and the careers we took…
Being a VFX artist is fundamentally based on mistrust.
This because schedules, pipelines, technology, creative calls… all have a native and naive instability to them that causes everyone to grow a genuine but beneficial lack of trust in the status quo. This is a fine balance act to build into your character. The VFX motto: “Love everyone but trust no one” is born on that.
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HDRI Resources
Read more: HDRI ResourcesText2Light
- https://www.cgtrader.com/free-3d-models/exterior/other/10-free-hdr-panoramas-created-with-text2light-zero-shot
- https://frozenburning.github.io/projects/text2light/
- https://github.com/FrozenBurning/Text2Light
Royalty free links
- https://locationtextures.com/panoramas/
- http://www.noahwitchell.com/freebies
- https://polyhaven.com/hdris
- https://hdrmaps.com/
- https://www.ihdri.com/
- https://hdrihaven.com/
- https://www.domeble.com/
- http://www.hdrlabs.com/sibl/archive.html
- https://www.hdri-hub.com/hdrishop/hdri
- http://noemotionhdrs.net/hdrevening.html
- https://www.openfootage.net/hdri-panorama/
- https://www.zwischendrin.com/en/browse/hdri
Nvidia GauGAN360
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Key/Fill ratios and scene composition using false colors
Read more: Key/Fill ratios and scene composition using false colors
To measure the contrast ratio you will need a light meter. The process starts with you measuring the main source of light, or the key light.
Get a reading from the brightest area on the face of your subject. Then, measure the area lit by the secondary light, or fill light. To make sense of what you have just measured you have to understand that the information you have just gathered is in F-stops, a measure of light. With each additional F-stop, for example going one stop from f/1.4 to f/2.0, you create a doubling of light. The reverse is also true; moving one stop from f/8.0 to f/5.6 results in a halving of the light.
Let’s say you grabbed a measurement from your key light of f/8.0. Then, when you measured your fill light area, you get a reading of f/4.0. This will lead you to a contrast ratio of 4:1 because there are two stops between f/4.0 and f/8.0 and each stop doubles the amount of light. In other words, two stops x twice the light per stop = four times as much light at f/8.0 than at f/4.0.
theslantedlens.com/2017/lighting-ratios-photo-video/
Examples in the post
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