COMPOSITION
DESIGN
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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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.
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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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Victor Perez – ACES Color Management in DaVinci Resolve
Read more: Victor Perez – ACES Color Management in DaVinci Resolvehttpv://www.youtube.com/watch?v=i–TS88-6xA
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Capturing textures albedo
Read more: Capturing textures albedoBuilding a Portable PBR Texture Scanner by Stephane Lb
http://rtgfx.com/pbr-texture-scanner/
How To Split Specular And Diffuse In Real Images, by John Hable
http://filmicworlds.com/blog/how-to-split-specular-and-diffuse-in-real-images/Capturing albedo using a Spectralon
https://www.activision.com/cdn/research/Real_World_Measurements_for_Call_of_Duty_Advanced_Warfare.pdfReal_World_Measurements_for_Call_of_Duty_Advanced_Warfare.pdf
Spectralon is a teflon-based pressed powderthat comes closest to being a pure Lambertian diffuse material that reflects 100% of all light. If we take an HDR photograph of the Spectralon alongside the material to be measured, we can derive thediffuse albedo of that material.
The process to capture diffuse reflectance is very similar to the one outlined by Hable.
1. We put a linear polarizing filter in front of the camera lens and a second linear polarizing filterin front of a modeling light or a flash such that the two filters are oriented perpendicular to eachother, i.e. cross polarized.
2. We place Spectralon close to and parallel with the material we are capturing and take brack-eted shots of the setup7. Typically, we’ll take nine photographs, from -4EV to +4EV in 1EVincrements.
3. We convert the bracketed shots to a linear HDR image. We found that many HDR packagesdo not produce an HDR image in which the pixel values are linear. PTGui is an example of apackage which does generate a linear HDR image. At this point, because of the cross polarization,the image is one of surface diffuse response.
4. We open the file in Photoshop and normalize the image by color picking the Spectralon, filling anew layer with that color and setting that layer to “Divide”. This sets the Spectralon to 1 in theimage. All other color values are relative to this so we can consider them as diffuse albedo.
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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
LIGHTING
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Sun cone angle (angular diameter) as perceived by earth viewers
Read more: Sun cone angle (angular diameter) as perceived by earth viewersAlso see:
https://www.pixelsham.com/2020/08/01/solid-angle-measures/
The cone angle of the sun refers to the angular diameter of the sun as observed from Earth, which is related to the apparent size of the sun in the sky.
The angular diameter of the sun, or the cone angle of the sunlight as perceived from Earth, is approximately 0.53 degrees on average. This value can vary slightly due to the elliptical nature of Earth’s orbit around the sun, but it generally stays within a narrow range.
Here’s a more precise breakdown:
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- Average Angular Diameter: About 0.53 degrees (31 arcminutes)
- Minimum Angular Diameter: Approximately 0.52 degrees (when Earth is at aphelion, the farthest point from the sun)
- Maximum Angular Diameter: Approximately 0.54 degrees (when Earth is at perihelion, the closest point to the sun)
This angular diameter remains relatively constant throughout the day because the sun’s distance from Earth does not change significantly over a single day.
To summarize, the cone angle of the sun’s light, or its angular diameter, is typically around 0.53 degrees, regardless of the time of day.
https://en.wikipedia.org/wiki/Angular_diameter
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