COMPOSITION
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Cinematographers Blueprint 300dpi poster
Read more: Cinematographers Blueprint 300dpi posterThe 300dpi digital poster is now available to all PixelSham.com subscribers.
If you have already subscribed and wish a copy, please send me a note through the contact page.
DESIGN
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Kristina Kashtanova – “This is how GPT-4 sees and hears itself”
“I used GPT-4 to describe itself. Then I used its description to generate an image, a video based on this image and a soundtrack.
Tools I used: GPT-4, Midjourney, Kaiber AI, Mubert, RunwayML
This is the description I used that GPT-4 had of itself as a prompt to text-to-image, image-to-video, and text-to-music. I put the video and sound together in RunwayML.
GPT-4 described itself as: “Imagine a sleek, metallic sphere with a smooth surface, representing the vast knowledge contained within the model. The sphere emits a soft, pulsating glow that shifts between various colors, symbolizing the dynamic nature of the AI as it processes information and generates responses. The sphere appears to float in a digital environment, surrounded by streams of data and code, reflecting the complex algorithms and computing power behind the AI”
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Turn Yourself Into an Action Figure Using ChatGPT
Read more: Turn Yourself Into an Action Figure Using ChatGPTChatGPT Action Figure Prompts:
Create an action figure from the photo. It must be visualised in a realistic way. There should be accessories next to the figure like a UX designer have, Macbook Pro, a camera, drawing tablet, headset etc. Add a hole to the top of the box in the action figure. Also write the text “UX Mate” and below it “Keep Learning! Keep Designing
Use this image to create a picture of a action figure toy of a construction worker in a blister package from head to toe with accessories including a hammer, a staple gun and a ladder. The package should read “Kirk The Handy Man”
Create a realistic image of a toy action figure box. The box should be designed in a toy-equipment/action-figure style, with a cut-out window at the top like classic action figure packaging. The main color of the box and moleskine notebook should match the color of my jacket (referenced visually). Add colorful Mexican skull decorations across the box for a vibrant and artistic flair. Inside the box, include a “Your name” action figure, posed heroically. Next to the figure, arrange the following “equipment” in a stylized layout: • item 1 • item 2 … On the box, write: “Your name” (bold title font) Underneath: “Your role or anything else” The entire scene should look like a real product mockup, highly realistic, lit like a studio product photo. On the box, write: “Your name” (bold title font) Underneath: “Your role or description” The entire scene should look like a real product mockup, highly realistic, lit like a studio product photo. Prompt on Kling AI The figure steps out of its toy packaging and begins walking forward. As he continues to walk, the camera gradually zooms out in sync with his movement.
“Create image. Create a toy of the person in the photo. Let it be an action figure. Next to the figure, there should be the toy’s equipment, each in its individual blisters. 1) a book called “Tecnoforma”. 2) A 3-headed dog with a tag that says “Troika” and a bone at its feet with word “austerity” written on it. 3) a three-headed Hydra with with a tag called “Geringonça”. 4) a book titled “D. Sebastião”. Don’t repeat the equipment under any circumstance. The card holding the blister should be strong orange. Also, on top of the box, write ‘Pedro Passos Coelho’ and underneath it, ‘PSD action figure’. The figure and equipment must all be inside blisters. Visualize this in a realistic way.”
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Mike Mitchell x Marvel x Mondo – Iconic portraits of Marvel’s huge stable of heroes and villains
Read more: Mike Mitchell x Marvel x Mondo – Iconic portraits of Marvel’s huge stable of heroes and villainshttps://mondoshop.com/blogs/gallery/16910155-mike-mitchell-x-marvel-x-mondo
https://time.com/69659/marvel-comics-mike-mitchell-artist-portraits/
COLOR
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Virtual Production volumes study
Read more: Virtual Production volumes studyColor Fidelity in LED Volumes
https://theasc.com/articles/color-fidelity-in-led-volumesVirtual Production Glossary
https://vpglossary.com/What is Virtual Production – In depth analysis
https://www.leadingledtech.com/what-is-a-led-virtual-production-studio-in-depth-technical-analysis/A comparison of LED panels for use in Virtual Production:
Findings and recommendations
https://eprints.bournemouth.ac.uk/36826/1/LED_Comparison_White_Paper%281%29.pdf -
Tim Kang – calibrated white light values in sRGB color space
8bit 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 -
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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Light and Matter : The 2018 theory of Physically-Based Rendering and Shading by Allegorithmic
Read more: Light and Matter : The 2018 theory of Physically-Based Rendering and Shading by Allegorithmicacademy.substance3d.com/courses/the-pbr-guide-part-1
academy.substance3d.com/courses/the-pbr-guide-part-2
Local copy:
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SecretWeapons MixBox – a practical library for paint-like digital color mixing
Read more: SecretWeapons MixBox – a practical library for paint-like digital color mixingInternally, Mixbox treats colors as real-life pigments using the Kubelka & Munk theory to predict realistic color behavior.
https://scrtwpns.com/mixbox/painter/
https://scrtwpns.com/mixbox.pdf
https://github.com/scrtwpns/mixbox
https://scrtwpns.com/mixbox/docs/
LIGHTING
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7 Easy Portrait Lighting Setups
Read more: 7 Easy Portrait Lighting SetupsButterfly
Loop
Rembrandt
Split
Rim
Broad
Short
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Photography basics: Exposure Value vs Photographic Exposure vs Il/Luminance vs Pixel luminance measurements
Read more: Photography basics: Exposure Value vs Photographic Exposure vs Il/Luminance vs Pixel luminance measurementsAlso see: https://www.pixelsham.com/2015/05/16/how-aperture-shutter-speed-and-iso-affect-your-photos/
In photography, exposure value (EV) is a number that represents a combination of a camera’s shutter speed and f-number, such that all combinations that yield the same exposure have the same EV (for any fixed scene luminance).
The EV concept was developed in an attempt to simplify choosing among combinations of equivalent camera settings. Although all camera settings with the same EV nominally give the same exposure, they do not necessarily give the same picture. EV is also used to indicate an interval on the photographic exposure scale. 1 EV corresponding to a standard power-of-2 exposure step, commonly referred to as a stop
EV 0 corresponds to an exposure time of 1 sec and a relative aperture of f/1.0. If the EV is known, it can be used to select combinations of exposure time and f-number.
Note EV does not equal to photographic exposure. Photographic Exposure is defined as how much light hits the camera’s sensor. It depends on the camera settings mainly aperture and shutter speed. Exposure value (known as EV) is a number that represents the exposure setting of the camera.
Thus, strictly, EV is not a measure of luminance (indirect or reflected exposure) or illuminance (incidental exposure); rather, an EV corresponds to a luminance (or illuminance) for which a camera with a given ISO speed would use the indicated EV to obtain the nominally correct exposure. Nonetheless, it is common practice among photographic equipment manufacturers to express luminance in EV for ISO 100 speed, as when specifying metering range or autofocus sensitivity.
The exposure depends on two things: how much light gets through the lenses to the camera’s sensor and for how long the sensor is exposed. The former is a function of the aperture value while the latter is a function of the shutter speed. Exposure value is a number that represents this potential amount of light that could hit the sensor. It is important to understand that exposure value is a measure of how exposed the sensor is to light and not a measure of how much light actually hits the sensor. The exposure value is independent of how lit the scene is. For example a pair of aperture value and shutter speed represents the same exposure value both if the camera is used during a very bright day or during a dark night.
Each exposure value number represents all the possible shutter and aperture settings that result in the same exposure. Although the exposure value is the same for different combinations of aperture values and shutter speeds the resulting photo can be very different (the aperture controls the depth of field while shutter speed controls how much motion is captured).
EV 0.0 is defined as the exposure when setting the aperture to f-number 1.0 and the shutter speed to 1 second. All other exposure values are relative to that number. Exposure values are on a base two logarithmic scale. This means that every single step of EV – plus or minus 1 – represents the exposure (actual light that hits the sensor) being halved or doubled.
https://www.streetdirectory.com/travel_guide/141307/photography/exposure_value_ev_and_exposure_compensation.html
Formula
https://en.wikipedia.org/wiki/Exposure_value
https://www.scantips.com/lights/math.html
which means 2EV = N² / t
where
- N is the relative aperture (f-number) Important: Note that f/stop values must first be squared in most calculations
- t is the exposure time (shutter speed) in seconds
EV 0 corresponds to an exposure time of 1 sec and an aperture of f/1.0.
Example: If f/16 and 1/4 second, then this is:
(N² / t) = (16 × 16 ÷ 1/4) = (16 × 16 × 4) = 1024.
Log₂(1024) is EV 10. Meaning, 210 = 1024.
Collecting photographic exposure using Light Meters
The exposure meter in the camera does not know whether the subject itself is bright or not. It simply measures the amount of light that comes in, and makes a guess based on that. The camera will aim for 18% gray, meaning if you take a photo of an entirely white surface, and an entirely black surface you should get two identical images which both are gray (at least in theory)
https://en.wikipedia.org/wiki/Light_meter
For reflected-light meters, camera settings are related to ISO speed and subject luminance by the reflected-light exposure equation:
where
- N is the relative aperture (f-number)
- t is the exposure time (“shutter speed”) in seconds
- L is the average scene luminance
- S is the ISO arithmetic speed
- K is the reflected-light meter calibration constant
For incident-light meters, camera settings are related to ISO speed and subject illuminance by the incident-light exposure equation:
where
- E is the illuminance (in lux)
- C is the incident-light meter calibration constant
Two values for K are in common use: 12.5 (Canon, Nikon, and Sekonic) and 14 (Minolta, Kenko, and Pentax); the difference between the two values is approximately 1/6 EV.
For C a value of 250 is commonly used.Nonetheless, it is common practice among photographic equipment manufacturers to also express luminance in EV for ISO 100 speed. Using K = 12.5, the relationship between EV at ISO 100 and luminance L is then :
L = 2(EV-3)
The situation with incident-light meters is more complicated than that for reflected-light meters, because the calibration constant C depends on the sensor type. Illuminance is measured with a flat sensor; a typical value for C is 250 with illuminance in lux. Using C = 250, the relationship between EV at ISO 100 and illuminance E is then :
E = 2.5 * 2(EV)
https://nofilmschool.com/2018/03/want-easier-and-faster-way-calculate-exposure-formula
Three basic factors go into the exposure formula itself instead: aperture, shutter, and ISO. Plus a light meter calibration constant.
f-stop²/shutter (in seconds) = lux * ISO/C
If you at least know four of those variables, you’ll be able to calculate the missing value.
So, say you want to figure out how much light you’re going to need in order to shoot at a certain f-stop. Well, all you do is plug in your values (you should know the f-stop, ISO, and your light meter calibration constant) into the formula below:
lux = C (f-stop²/shutter (in seconds))/ISO
Exposure Value Calculator:
https://snapheadshots.com/resources/exposure-and-light-calculator
https://www.scantips.com/lights/exposurecalc.html
https://www.pointsinfocus.com/tools/exposure-settings-ev-calculator/#google_vignette
From that perspective, an exposure stop is a measurement of Exposure and provides a universal linear scale to measure the increase and decrease in light, exposed to the image sensor, due to changes in shutter speed, iso & f-stop.
+-1 stop is a doubling or halving of the amount of light let in when taking a photo.
1 EV is just another way to say one stop of exposure change.One major use of EV (Exposure Value) is just to measure any change of exposure, where one EV implies a change of one stop of exposure. Like when we compensate our picture in the camera.
If the picture comes out too dark, our manual exposure could correct the next one by directly adjusting one of the three exposure controls (f/stop, shutter speed, or ISO). Or if using camera automation, the camera meter is controlling it, but we might apply +1 EV exposure compensation (or +1 EV flash compensation) to make the result goal brighter, as desired. This use of 1 EV is just another way to say one stop of exposure change.
On a perfect day the difference from sampling the sky vs the sun exposure with diffusing spot meters is about 3.2 exposure difference.
~15.4 EV for the sun ~12.2 EV for the sky
That is as a ballpark. All still influenced by surroundings, accuracy parameters, fov of the sensor…
EV calculator
https://www.scantips.com/lights/evchart.html#calc
http://www.fredparker.com/ultexp1.htm
Exposure value is basically used to indicate an interval on the photographic exposure scale, with a difference of 1 EV corresponding to a standard power-of-2 exposure step, also commonly referred to as a “stop”.
https://contrastly.com/a-guide-to-understanding-exposure-value-ev/
Retrieving photographic exposure from an image
All you can hope to measure with your camera and some images is the relative reflected luminance. Even if you have the camera settings. https://en.wikipedia.org/wiki/Relative_luminance
If you REALLY want to know the amount of light in absolute radiometric units, you’re going to need to use some kind of absolute light meter or measured light source to calibrate your camera. For references on how to do this, see: Section 2.5 Obtaining Absolute Radiance from http://www.pauldebevec.com/Research/HDR/debevec-siggraph97.pdf
IF you are still trying to gauge relative brightness, the level of the sun in Nuke can vary, but it should be in the thousands. Ie: between 30,000 and 65,0000 rgb value depending on time of the day, season and atmospherics.
The values for a 12 o’clock sun, with the sun sampled at EV 15.5 (shutter 1/30, ISO 100, F22) is 32.000 RGB max values (or 32,000 pixel luminance).
The thing to keep an eye for is the level of contrast between sunny side/fill side. The terminator should be quite obvious, there can be up to 3 stops difference between fill/key in sunny lit objects.Note: In Foundry’s Nuke, the software will map 18% gray to whatever your center f/stop is set to in the viewer settings (f/8 by default… change that to EV by following the instructions below).
You can experiment with this by attaching an Exposure node to a Constant set to 0.18, setting your viewer read-out to Spotmeter, and adjusting the stops in the node up and down. You will see that a full stop up or down will give you the respective next value on the aperture scale (f8, f11, f16 etc.).
One stop doubles or halves the amount or light that hits the filmback/ccd, so everything works in powers of 2.
So starting with 0.18 in your constant, you will see that raising it by a stop will give you .36 as a floating point number (in linear space), while your f/stop will be f/11 and so on.If you set your center stop to 0 (see below) you will get a relative readout in EVs, where EV 0 again equals 18% constant gray.
Note: make sure to set your Nuke read node to ‘raw data’In other words. Setting the center f-stop to 0 means that in a neutral plate, the middle gray in the macbeth chart will equal to exposure value 0. EV 0 corresponds to an exposure time of 1 sec and an aperture of f/1.0.
To switch Foundry’s Nuke’s SpotMeter to return the EV of an image, click on the main viewport, and then press s, this opens the viewer’s properties. Now set the center f-stop to 0 in there. And the SpotMeter in the viewport will change from aperture and fstops to EV.
If you are trying to gauge the EV from the pixel luminance in the image:
– Setting the center f-stop to 0 means that in a neutral plate, the middle 18% gray will equal to exposure value 0.
– So if EV 0 = 0.18 middle gray in nuke which equal to a pixel luminance of 0.18, doubling that value, doubles the EV..18 pixel luminance = 0EV .36 pixel luminance = 1EV .72 pixel luminance = 2EV 1.46 pixel luminance = 3EV ...
This is a Geometric Progression function: xn = ar(n-1)
The most basic example of this function is 1,2,4,8,16,32,… The sequence starts at 1 and doubles each time, so
- a=1 (the first term)
- r=2 (the “common ratio” between terms is a doubling)
And we get:
{a, ar, ar2, ar3, … }
= {1, 1×2, 1×22, 1×23, … }
= {1, 2, 4, 8, … }
In this example the function translates to: n = 2(n-1)
You can graph this curve through this expression: x = 2(y-1) :You can go back and forth between the two values through a geometric progression function and a log function:
(Note: in a spreadsheet this is: = POWER(2; cell# -1) and =LOG(cell#, 2)+1) )
2(y-1) log2(x)+1 x y 1 1 2 2 4 3 8 4 16 5 32 6 64 7 128 8 256 9 512 10 1024 11 2048 12 4096 13 Translating this into a geometric progression between an image pixel luminance and EV:
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What’s the Difference Between Ray Casting, Ray Tracing, Path Tracing and Rasterization? Physical light tracing…
RASTERIZATION
Rasterisation (or rasterization) is the task of taking the information described in a vector graphics format OR the vertices of triangles making 3D shapes and converting them into a raster image (a series of pixels, dots or lines, which, when displayed together, create the image which was represented via shapes), or in other words “rasterizing” vectors or 3D models onto a 2D plane for display on a computer screen.For each triangle of a 3D shape, you project the corners of the triangle on the virtual screen with some math (projective geometry). Then you have the position of the 3 corners of the triangle on the pixel screen. Those 3 points have texture coordinates, so you know where in the texture are the 3 corners. The cost is proportional to the number of triangles, and is only a little bit affected by the screen resolution.
In computer graphics, a raster graphics or bitmap image is a dot matrix data structure that represents a generally rectangular grid of pixels (points of color), viewable via a monitor, paper, or other display medium.
With rasterization, objects on the screen are created from a mesh of virtual triangles, or polygons, that create 3D models of objects. A lot of information is associated with each vertex, including its position in space, as well as information about color, texture and its “normal,” which is used to determine the way the surface of an object is facing.
Computers then convert the triangles of the 3D models into pixels, or dots, on a 2D screen. Each pixel can be assigned an initial color value from the data stored in the triangle vertices.
Further pixel processing or “shading,” including changing pixel color based on how lights in the scene hit the pixel, and applying one or more textures to the pixel, combine to generate the final color applied to a pixel.
The main advantage of rasterization is its speed. However, rasterization is simply the process of computing the mapping from scene geometry to pixels and does not prescribe a particular way to compute the color of those pixels. So it cannot take shading, especially the physical light, into account and it cannot promise to get a photorealistic output. That’s a big limitation of rasterization.
There are also multiple problems:
If you have two triangles one is behind the other, you will draw twice all the pixels. you only keep the pixel from the triangle that is closer to you (Z-buffer), but you still do the work twice.
The borders of your triangles are jagged as it is hard to know if a pixel is in the triangle or out. You can do some smoothing on those, that is anti-aliasing.
You have to handle every triangles (including the ones behind you) and then see that they do not touch the screen at all. (we have techniques to mitigate this where we only look at triangles that are in the field of view)
Transparency is hard to handle (you can’t just do an average of the color of overlapping transparent triangles, you have to do it in the right order)
RAY CASTING
It is almost the exact reverse of rasterization: you start from the virtual screen instead of the vector or 3D shapes, and you project a ray, starting from each pixel of the screen, until it intersect with a triangle.The cost is directly correlated to the number of pixels in the screen and you need a really cheap way of finding the first triangle that intersect a ray. In the end, it is more expensive than rasterization but it will, by design, ignore the triangles that are out of the field of view.
You can use it to continue after the first triangle it hit, to take a little bit of the color of the next one, etc… This is useful to handle the border of the triangle cleanly (less jagged) and to handle transparency correctly.
RAYTRACING
Same idea as ray casting except once you hit a triangle you reflect on it and go into a different direction. The number of reflection you allow is the “depth” of your ray tracing. The color of the pixel can be calculated, based off the light source and all the polygons it had to reflect off of to get to that screen pixel.The easiest way to think of ray tracing is to look around you, right now. The objects you’re seeing are illuminated by beams of light. Now turn that around and follow the path of those beams backwards from your eye to the objects that light interacts with. That’s ray tracing.
Ray tracing is eye-oriented process that needs walking through each pixel looking for what object should be shown there, which is also can be described as a technique that follows a beam of light (in pixels) from a set point and simulates how it reacts when it encounters objects.
Compared with rasterization, ray tracing is hard to be implemented in real time, since even one ray can be traced and processed without much trouble, but after one ray bounces off an object, it can turn into 10 rays, and those 10 can turn into 100, 1000…The increase is exponential, and the the calculation for all these rays will be time consuming.
Historically, computer hardware hasn’t been fast enough to use these techniques in real time, such as in video games. Moviemakers can take as long as they like to render a single frame, so they do it offline in render farms. Video games have only a fraction of a second. As a result, most real-time graphics rely on the another technique called rasterization.
PATH TRACING
Path tracing can be used to solve more complex lighting situations.
Path tracing is a type of ray tracing. When using path tracing for rendering, the rays only produce a single ray per bounce. The rays do not follow a defined line per bounce (to a light, for example), but rather shoot off in a random direction. The path tracing algorithm then takes a random sampling of all of the rays to create the final image. This results in sampling a variety of different types of lighting.When a ray hits a surface it doesn’t trace a path to every light source, instead it bounces the ray off the surface and keeps bouncing it until it hits a light source or exhausts some bounce limit.
It then calculates the amount of light transferred all the way to the pixel, including any color information gathered from surfaces along the way.
It then averages out the values calculated from all the paths that were traced into the scene to get the final pixel color value.It requires a ton of computing power and if you don’t send out enough rays per pixel or don’t trace the paths far enough into the scene then you end up with a very spotty image as many pixels fail to find any light sources from their rays. So when you increase the the samples per pixel, you can see the image quality becomes better and better.
Ray tracing tends to be more efficient than path tracing. Basically, the render time of a ray tracer depends on the number of polygons in the scene. The more polygons you have, the longer it will take.
Meanwhile, the rendering time of a path tracer can be indifferent to the number of polygons, but it is related to light situation: If you add a light, transparency, translucence, or other shader effects, the path tracer will slow down considerably.blogs.nvidia.com/blog/2018/03/19/whats-difference-between-ray-tracing-rasterization/
https://en.wikipedia.org/wiki/Rasterisation
https://www.quora.com/Whats-the-difference-between-ray-tracing-and-path-tracing
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Black Body color aka the Planckian Locus curve for white point eye perception
Read more: Black Body color aka the Planckian Locus curve for white point eye perceptionhttp://en.wikipedia.org/wiki/Black-body_radiation
Black-body radiation is the type of electromagnetic radiation within or surrounding a body in thermodynamic equilibrium with its environment, or emitted by a black body (an opaque and non-reflective body) held at constant, uniform temperature. The radiation has a specific spectrum and intensity that depends only on the temperature of the body.
A black-body at room temperature appears black, as most of the energy it radiates is infra-red and cannot be perceived by the human eye. At higher temperatures, black bodies glow with increasing intensity and colors that range from dull red to blindingly brilliant blue-white as the temperature increases.
The Black Body Ultraviolet Catastrophe Experiment
In photography, color temperature describes the spectrum of light which is radiated from a “blackbody” with that surface temperature. A blackbody is an object which absorbs all incident light — neither reflecting it nor allowing it to pass through.
The Sun closely approximates a black-body radiator. Another rough analogue of blackbody radiation in our day to day experience might be in heating a metal or stone: these are said to become “red hot” when they attain one temperature, and then “white hot” for even higher temperatures. Similarly, black bodies at different temperatures also have varying color temperatures of “white light.”
Despite its name, light which may appear white does not necessarily contain an even distribution of colors across the visible spectrum.
Although planets and stars are neither in thermal equilibrium with their surroundings nor perfect black bodies, black-body radiation is used as a first approximation for the energy they emit. Black holes are near-perfect black bodies, and it is believed that they emit black-body radiation (called Hawking radiation), with a temperature that depends on the mass of the hole.
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What light is best to illuminate gems for resale
www.palagems.com/gem-lighting2
Artificial light sources, not unlike the diverse phases of natural light, vary considerably in their properties. As a result, some lamps render an object’s color better than others do.
The most important criterion for assessing the color-rendering ability of any lamp is its spectral power distribution curve.
Natural daylight varies too much in strength and spectral composition to be taken seriously as a lighting standard for grading and dealing colored stones. For anything to be a standard, it must be constant in its properties, which natural light is not.
For dealers in particular to make the transition from natural light to an artificial light source, that source must offer:
1- A degree of illuminance at least as strong as the common phases of natural daylight.
2- Spectral properties identical or comparable to a phase of natural daylight.A source combining these two things makes gems appear much the same as when viewed under a given phase of natural light. From the viewpoint of many dealers, this corresponds to a naturalappearance.
The 6000° Kelvin xenon short-arc lamp appears closest to meeting the criteria for a standard light source. Besides the strong illuminance this lamp affords, its spectrum is very similar to CIE standard illuminants of similar color temperature.
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