COMPOSITION
DESIGN
- 
Hand made Settlers of Catan board
Read more: Hand made Settlers of Catan boardtrytrytry.de/2016/07/mega-diy-siedler-von-catan-in-3d/
https://www.youtube.com/watch?v=Lqww2yZkeh0
 
COLOR
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A Brief History of Color in Art
Read more: A Brief History of Color in Artwww.artsy.net/article/the-art-genome-project-a-brief-history-of-color-in-art
Of all the pigments that have been banned over the centuries, the color most missed by painters is likely Lead White.
This hue could capture and reflect a gleam of light like no other, though its production was anything but glamorous. The 17th-century Dutch method for manufacturing the pigment involved layering cow and horse manure over lead and vinegar. After three months in a sealed room, these materials would combine to create flakes of pure white. While scientists in the late 19th century identified lead as poisonous, it wasn’t until 1978 that the United States banned the production of lead white paint.
More reading:
www.canva.com/learn/color-meanings/https://www.infogrades.com/history-events-infographics/bizarre-history-of-colors/
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mmColorTarget – Nuke Gizmo for color matching a MacBeth chart
Read more: mmColorTarget – Nuke Gizmo for color matching a MacBeth charthttps://www.marcomeyer-vfx.de/posts/2014-04-11-mmcolortarget-nuke-gizmo/
https://www.marcomeyer-vfx.de/posts/mmcolortarget-nuke-gizmo/
https://vimeo.com/9.1652466e+07
https://www.nukepedia.com/gizmos/colour/mmcolortarget
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VES Cinematic Color – Motion-Picture Color Management
Read more: VES Cinematic Color – Motion-Picture Color ManagementThis paper presents an introduction to the color pipelines behind modern feature-film visual-effects and animation.
Authored by Jeremy Selan, and reviewed by the members of the VES Technology Committee including Rob Bredow, Dan Candela, Nick Cannon, Paul Debevec, Ray Feeney, Andy Hendrickson, Gautham Krishnamurti, Sam Richards, Jordan Soles, and Sebastian Sylwan.
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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.

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Colour – MacBeth Chart Checker Detection
Read more: Colour – MacBeth Chart Checker Detectiongithub.com/colour-science/colour-checker-detection
A Python package implementing various colour checker detection algorithms and related utilities.

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StudioBinder.com – CRI color rendering index
Read more: StudioBinder.com – CRI color rendering indexwww.studiobinder.com/blog/what-is-color-rendering-index
“The Color Rendering Index is a measurement of how faithfully a light source reveals the colors of whatever it illuminates, it describes the ability of a light source to reveal the color of an object, as compared to the color a natural light source would provide. The highest possible CRI is 100. A CRI of 100 generally refers to a perfect black body, like a tungsten light source or the sun. ”
www.pixelsham.com/2021/04/28/types-of-film-lights-and-their-efficiency
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OpenColorIO standard
Read more: OpenColorIO standardhttps://www.provideocoalition.com/color-management-part-11-introducing-opencolorio/
OpenColorIO (OCIO) is a new open source project from Sony Imageworks.
Based on development started in 2003, OCIO enables color transforms and image display to be handled in a consistent manner across multiple graphics applications. Unlike other color management solutions, OCIO is geared towards motion-picture post production, with an emphasis on visual effects and animation color pipelines.
 
LIGHTING
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Disney’s Moana Island Scene – Free data set
Read more: Disney’s Moana Island Scene – Free data sethttps://www.disneyanimation.com/resources/moana-island-scene/
This data set contains everything necessary to render a version of the Motunui island featured in the 2016 film Moana.
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Convert between light exposure and intensity
Read more: Convert between light exposure and intensityimport math,sys def Exposure2Intensity(exposure): exp = float(exposure) result = math.pow(2,exp) print(result) Exposure2Intensity(0) def Intensity2Exposure(intensity): inarg = float(intensity) if inarg == 0: print("Exposure of zero intensity is undefined.") return if inarg < 1e-323: inarg = max(inarg, 1e-323) print("Exposure of negative intensities is undefined. Clamping to a very small value instead (1e-323)") result = math.log(inarg, 2) print(result) Intensity2Exposure(0.1)Why Exposure?
Exposure is a stop value that multiplies the intensity by 2 to the power of the stop. Increasing exposure by 1 results in double the amount of light.
Artists think in “stops.” Doubling or halving brightness is easy math and common in grading and look-dev.
Exposure counts doublings in whole stops:- +1 stop = ×2 brightness
 - −1 stop = ×0.5 brightness
 
This gives perceptually even controls across both bright and dark values.
Why Intensity?
Intensity is linear.
It’s what render engines and compositors expect when:- Summing values
 - Averaging pixels
 - Multiplying or filtering pixel data
 
Use intensity when you need the actual math on pixel/light data.
Formulas (from your Python)
- Intensity from exposure: intensity = 2**exposure
 - Exposure from intensity: exposure = log₂(intensity)
 
Guardrails:
- Intensity must be > 0 to compute exposure.
 - If intensity = 0 → exposure is undefined.
 - Clamp tiny values (e.g. 
1e−323) before using log₂. 
Use Exposure (stops) when…
- You want artist-friendly sliders (−5…+5 stops)
 - Adjusting look-dev or grading in even stops
 - Matching plates with quick ±1 stop tweaks
 - Tweening brightness changes smoothly across ranges
 
Use Intensity (linear) when…
- Storing raw pixel/light values
 - Multiplying textures or lights by a gain
 - Performing sums, averages, and filters
 - Feeding values to render engines expecting linear data
 
Examples
- +2 stops → 2**2 = 4.0 (×4)
 - +1 stop → 2**1 = 2.0 (×2)
 - 0 stop → 2**0 = 1.0 (×1)
 - −1 stop → 2**(−1) = 0.5 (×0.5)
 - −2 stops → 2**(−2) = 0.25 (×0.25)
 - Intensity 0.1 → exposure = log₂(0.1) ≈ −3.32
 
Rule of thumb
Think in stops (exposure) for controls and matching.
Compute in linear (intensity) for rendering and math. - 
Narcis Calin’s Galaxy Engine – A free, open source simulation software
Read more: Narcis Calin’s Galaxy Engine – A free, open source simulation softwareThis 2025 I decided to start learning how to code, so I installed Visual Studio and I started looking into C++. After days of watching tutorials and guides about the basics of C++ and programming, I decided to make something physics-related. I started with a dot that fell to the ground and then I wanted to simulate gravitational attraction, so I made 2 circles attracting each other. I thought it was really cool to see something I made with code actually work, so I kept building on top of that small, basic program. And here we are after roughly 8 months of learning programming. This is Galaxy Engine, and it is a simulation software I have been making ever since I started my learning journey. It currently can simulate gravity, dark matter, galaxies, the Big Bang, temperature, fluid dynamics, breakable solids, planetary interactions, etc. The program can run many tens of thousands of particles in real time on the CPU thanks to the Barnes-Hut algorithm, mixed with Morton curves. It also includes its own PBR 2D path tracer with BVH optimizations. The path tracer can simulate a bunch of stuff like diffuse lighting, specular reflections, refraction, internal reflection, fresnel, emission, dispersion, roughness, IOR, nested IOR and more! I tried to make the path tracer closer to traditional 3D render engines like V-Ray. I honestly never imagined I would go this far with programming, and it has been an amazing learning experience so far. I think that mixing this knowledge with my 3D knowledge can unlock countless new possibilities. In case you are curious about Galaxy Engine, I made it completely free and Open-Source so that anyone can build and compile it locally! You can find the source code in GitHub
https://github.com/NarcisCalin/Galaxy-Engine
 
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