COMPOSITION
DESIGN
COLOR
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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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3D Lighting Tutorial by Amaan Kram
Read more: 3D Lighting Tutorial by Amaan Kramhttp://www.amaanakram.com/lightingT/part1.htm
The goals of lighting in 3D computer graphics are more or less the same as those of real world lighting.
Lighting serves a basic function of bringing out, or pushing back the shapes of objects visible from the camera’s view.
It gives a two-dimensional image on the monitor an illusion of the third dimension-depth.But it does not just stop there. It gives an image its personality, its character. A scene lit in different ways can give a feeling of happiness, of sorrow, of fear etc., and it can do so in dramatic or subtle ways. Along with personality and character, lighting fills a scene with emotion that is directly transmitted to the viewer.
Trying to simulate a real environment in an artificial one can be a daunting task. But even if you make your 3D rendering look absolutely photo-realistic, it doesn’t guarantee that the image carries enough emotion to elicit a “wow” from the people viewing it.
Making 3D renderings photo-realistic can be hard. Putting deep emotions in them can be even harder. However, if you plan out your lighting strategy for the mood and emotion that you want your rendering to express, you make the process easier for yourself.
Each light source can be broken down in to 4 distinct components and analyzed accordingly.
· Intensity
· Direction
· Color
· SizeThe overall thrust of this writing is to produce photo-realistic images by applying good lighting techniques.
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What is OLED and what can it do for your TV
Read more: What is OLED and what can it do for your TVhttps://www.cnet.com/news/what-is-oled-and-what-can-it-do-for-your-tv/
OLED stands for Organic Light Emitting Diode. Each pixel in an OLED display is made of a material that glows when you jab it with electricity. Kind of like the heating elements in a toaster, but with less heat and better resolution. This effect is called electroluminescence, which is one of those delightful words that is big, but actually makes sense: “electro” for electricity, “lumin” for light and “escence” for, well, basically “essence.”
OLED TV marketing often claims “infinite” contrast ratios, and while that might sound like typical hyperbole, it’s one of the extremely rare instances where such claims are actually true. Since OLED can produce a perfect black, emitting no light whatsoever, its contrast ratio (expressed as the brightest white divided by the darkest black) is technically infinite.
OLED is the only technology capable of absolute blacks and extremely bright whites on a per-pixel basis. LCD definitely can’t do that, and even the vaunted, beloved, dearly departed plasma couldn’t do absolute blacks.
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Photography Basics : Spectral Sensitivity Estimation Without a Camera
Read more: Photography Basics : Spectral Sensitivity Estimation Without a Camerahttps://color-lab-eilat.github.io/Spectral-sensitivity-estimation-web/
A number of problems in computer vision and related fields would be mitigated if camera spectral sensitivities were known. As consumer cameras are not designed for high-precision visual tasks, manufacturers do not disclose spectral sensitivities. Their estimation requires a costly optical setup, which triggered researchers to come up with numerous indirect methods that aim to lower cost and complexity by using color targets. However, the use of color targets gives rise to new complications that make the estimation more difficult, and consequently, there currently exists no simple, low-cost, robust go-to method for spectral sensitivity estimation that non-specialized research labs can adopt. Furthermore, even if not limited by hardware or cost, researchers frequently work with imagery from multiple cameras that they do not have in their possession.
To provide a practical solution to this problem, we propose a framework for spectral sensitivity estimation that not only does not require any hardware (including a color target), but also does not require physical access to the camera itself. Similar to other work, we formulate an optimization problem that minimizes a two-term objective function: a camera-specific term from a system of equations, and a universal term that bounds the solution space.
Different than other work, we utilize publicly available high-quality calibration data to construct both terms. We use the colorimetric mapping matrices provided by the Adobe DNG Converter to formulate the camera-specific system of equations, and constrain the solutions using an autoencoder trained on a database of ground-truth curves. On average, we achieve reconstruction errors as low as those that can arise due to manufacturing imperfections between two copies of the same camera. We provide predicted sensitivities for more than 1,000 cameras that the Adobe DNG Converter currently supports, and discuss which tasks can become trivial when camera responses are available.
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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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The Forbidden colors – Red-Green & Blue-Yellow: The Stunning Colors You Can’t See
Read more: The Forbidden colors – Red-Green & Blue-Yellow: The Stunning Colors You Can’t Seewww.livescience.com/17948-red-green-blue-yellow-stunning-colors.html
While the human eye has red, green, and blue-sensing cones, those cones are cross-wired in the retina to produce a luminance channel plus a red-green and a blue-yellow channel, and it’s data in that color space (known technically as “LAB”) that goes to the brain. That’s why we can’t perceive a reddish-green or a yellowish-blue, whereas such colors can be represented in the RGB color space used by digital cameras.
https://en.rockcontent.com/blog/the-use-of-yellow-in-data-design
The back of the retina is covered in light-sensitive neurons known as cone cells and rod cells. There are three types of cone cells, each sensitive to different ranges of light. These ranges overlap, but for convenience the cones are referred to as blue (short-wavelength), green (medium-wavelength), and red (long-wavelength). The rod cells are primarily used in low-light situations, so we’ll ignore those for now.
When light enters the eye and hits the cone cells, the cones get excited and send signals to the brain through the visual cortex. Different wavelengths of light excite different combinations of cones to varying levels, which generates our perception of color. You can see that the red cones are most sensitive to light, and the blue cones are least sensitive. The sensitivity of green and red cones overlaps for most of the visible spectrum.
Here’s how your brain takes the signals of light intensity from the cones and turns it into color information. To see red or green, your brain finds the difference between the levels of excitement in your red and green cones. This is the red-green channel.
To get “brightness,” your brain combines the excitement of your red and green cones. This creates the luminance, or black-white, channel. To see yellow or blue, your brain then finds the difference between this luminance signal and the excitement of your blue cones. This is the yellow-blue channel.
From the calculations made in the brain along those three channels, we get four basic colors: blue, green, yellow, and red. Seeing blue is what you experience when low-wavelength light excites the blue cones more than the green and red.
Seeing green happens when light excites the green cones more than the red cones. Seeing red happens when only the red cones are excited by high-wavelength light.
Here’s where it gets interesting. Seeing yellow is what happens when BOTH the green AND red cones are highly excited near their peak sensitivity. This is the biggest collective excitement that your cones ever have, aside from seeing pure white.
Notice that yellow occurs at peak intensity in the graph to the right. Further, the lens and cornea of the eye happen to block shorter wavelengths, reducing sensitivity to blue and violet light.
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What Is The Resolution and view coverage Of The human Eye. And what distance is TV at best?
Read more: What Is The Resolution and view coverage Of The human Eye. And what distance is TV at best?
https://www.discovery.com/science/mexapixels-in-human-eye
About 576 megapixels for the entire field of view.
Consider a view in front of you that is 90 degrees by 90 degrees, like looking through an open window at a scene. The number of pixels would be:
90 degrees * 60 arc-minutes/degree * 1/0.3 * 90 * 60 * 1/0.3 = 324,000,000 pixels (324 megapixels).At any one moment, you actually do not perceive that many pixels, but your eye moves around the scene to see all the detail you want. But the human eye really sees a larger field of view, close to 180 degrees. Let’s be conservative and use 120 degrees for the field of view. Then we would see:
120 * 120 * 60 * 60 / (0.3 * 0.3) = 576 megapixels.
Or.
7 megapixels for the 2 degree focus arc… + 1 megapixel for the rest.
https://clarkvision.com/articles/eye-resolution.html
Details in the post
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colorhunt.co
Read more: colorhunt.coColor Hunt is a free and open platform for color inspiration with thousands of trendy hand-picked color palettes.
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Anders Langlands – Render Color Spaces
Read more: Anders Langlands – Render Color Spaceshttps://www.colour-science.org/anders-langlands/
This page compares images rendered in Arnold using spectral rendering and different sets of colourspace primaries: Rec.709, Rec.2020, ACES and DCI-P3. The SPD data for the GretagMacbeth Color Checker are the measurements of Noburu Ohta, taken from Mansencal, Mauderer and Parsons (2014) colour-science.org.
![[gamma correction test]](http://www.madore.org/~david/misc/color/gammatest.png "sRGB gamma correction test")
LIGHTING
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What is physically correct lighting all about?
Read more: What is physically correct lighting all about?http://gamedev.stackexchange.com/questions/60638/what-is-physically-correct-lighting-all-about
2012-08 Nathan Reed wrote:
Physically-based shading means leaving behind phenomenological models, like the Phong shading model, which are simply built to “look good” subjectively without being based on physics in any real way, and moving to lighting and shading models that are derived from the laws of physics and/or from actual measurements of the real world, and rigorously obey physical constraints such as energy conservation.
For example, in many older rendering systems, shading models included separate controls for specular highlights from point lights and reflection of the environment via a cubemap. You could create a shader with the specular and the reflection set to wildly different values, even though those are both instances of the same physical process. In addition, you could set the specular to any arbitrary brightness, even if it would cause the surface to reflect more energy than it actually received.
In a physically-based system, both the point light specular and the environment reflection would be controlled by the same parameter, and the system would be set up to automatically adjust the brightness of both the specular and diffuse components to maintain overall energy conservation. Moreover you would want to set the specular brightness to a realistic value for the material you’re trying to simulate, based on measurements.
Physically-based lighting or shading includes physically-based BRDFs, which are usually based on microfacet theory, and physically correct light transport, which is based on the rendering equation (although heavily approximated in the case of real-time games).
It also includes the necessary changes in the art process to make use of these features. Switching to a physically-based system can cause some upsets for artists. First of all it requires full HDR lighting with a realistic level of brightness for light sources, the sky, etc. and this can take some getting used to for the lighting artists. It also requires texture/material artists to do some things differently (particularly for specular), and they can be frustrated by the apparent loss of control (e.g. locking together the specular highlight and environment reflection as mentioned above; artists will complain about this). They will need some time and guidance to adapt to the physically-based system.
On the plus side, once artists have adapted and gained trust in the physically-based system, they usually end up liking it better, because there are fewer parameters overall (less work for them to tweak). Also, materials created in one lighting environment generally look fine in other lighting environments too. This is unlike more ad-hoc models, where a set of material parameters might look good during daytime, but it comes out ridiculously glowy at night, or something like that.
Here are some resources to look at for physically-based lighting in games:
SIGGRAPH 2013 Physically Based Shading Course, particularly the background talk by Naty Hoffman at the beginning. You can also check out the previous incarnations of this course for more resources.
Sébastien Lagarde, Adopting a physically-based shading model and Feeding a physically-based shading model
And of course, I would be remiss if I didn’t mention Physically-Based Rendering by Pharr and Humphreys, an amazing reference on this whole subject and well worth your time, although it focuses on offline rather than real-time rendering.
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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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The Color of Infinite Temperature
Read more: The Color of Infinite TemperatureThis is the color of something infinitely hot.
Of course you’d instantly be fried by gamma rays of arbitrarily high frequency, but this would be its spectrum in the visible range.
johncarlosbaez.wordpress.com/2022/01/16/the-color-of-infinite-temperature/
This is also the color of a typical neutron star. They’re so hot they look the same.
It’s also the color of the early Universe!This was worked out by David Madore.
The color he got is sRGB(148,177,255).
www.htmlcsscolor.com/hex/94B1FFAnd according to the experts who sip latte all day and make up names for colors, this color is called ‘Perano’.
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Terminators and Iron Men: HDRI, Image-based lighting and physical shading at ILM – Siggraph 2010
Read more: Terminators and Iron Men: HDRI, Image-based lighting and physical shading at ILM – Siggraph 2010
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