COMPOSITION
DESIGN
COLOR
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PTGui 13 beta adds control through a Patch Editor
Additions:
- Patch Editor (PTGui Pro)
- DNG output
- Improved RAW / DNG handling
- JPEG 2000 support
- Performance improvements
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GretagMacbeth Color Checker Numeric Values and Middle Gray
Read more: GretagMacbeth Color Checker Numeric Values and Middle GrayThe human eye perceives half scene brightness not as the linear 50% of the present energy (linear nature values) but as 18% of the overall brightness. We are biased to perceive more information in the dark and contrast areas. A Macbeth chart helps with calibrating back into a photographic capture into this “human perspective” of the world.
https://en.wikipedia.org/wiki/Middle_gray
In photography, painting, and other visual arts, middle gray or middle grey is a tone that is perceptually about halfway between black and white on a lightness scale in photography and printing, it is typically defined as 18% reflectance in visible light
Light meters, cameras, and pictures are often calibrated using an 18% gray card[4][5][6] or a color reference card such as a ColorChecker. On the assumption that 18% is similar to the average reflectance of a scene, a grey card can be used to estimate the required exposure of the film.
https://en.wikipedia.org/wiki/ColorChecker
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 independently, 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). Thus enters the Macbeth chart.
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Note that Chroma Key Green is reasonably close to an 18% gray reflectance.
http://www.rags-int-inc.com/PhotoTechStuff/MacbethTarget/
https://upload.wikimedia.org/wikipedia/commons/b/b4/CIE1931xy_ColorChecker_SMIL.svg
RGB coordinates of the Macbeth ColorChecker
https://pdfs.semanticscholar.org/0e03/251ad1e6d3c3fb9cb0b1f9754351a959e065.pdf
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Björn Ottosson – How software gets color wrong
Read more: Björn Ottosson – How software gets color wronghttps://bottosson.github.io/posts/colorwrong/
Most software around us today are decent at accurately displaying colors. Processing of colors is another story unfortunately, and is often done badly.
To understand what the problem is, let’s start with an example of three ways of blending green and magenta:
- Perceptual blend – A smooth transition using a model designed to mimic human perception of color. The blending is done so that the perceived brightness and color varies smoothly and evenly.
- Linear blend – A model for blending color based on how light behaves physically. This type of blending can occur in many ways naturally, for example when colors are blended together by focus blur in a camera or when viewing a pattern of two colors at a distance.
- sRGB blend – This is how colors would normally be blended in computer software, using sRGB to represent the colors.
Let’s look at some more examples of blending of colors, to see how these problems surface more practically. The examples use strong colors since then the differences are more pronounced. This is using the same three ways of blending colors as the first example.
Instead of making it as easy as possible to work with color, most software make it unnecessarily hard, by doing image processing with representations not designed for it. Approximating the physical behavior of light with linear RGB models is one easy thing to do, but more work is needed to create image representations tailored for image processing and human perception.
Also see:
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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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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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If a blind person gained sight, could they recognize objects previously touched?
Blind people who regain their sight may find themselves in a world they don’t immediately comprehend. “It would be more like a sighted person trying to rely on tactile information,” Moore says.
Learning to see is a developmental process, just like learning language, Prof Cathleen Moore continues. “As far as vision goes, a three-and-a-half year old child is already a well-calibrated system.”
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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.
LIGHTING
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Open Source Nvidia Omniverse
Read more: Open Source Nvidia Omniverseblogs.nvidia.com/blog/2019/03/18/omniverse-collaboration-platform/
developer.nvidia.com/nvidia-omniverse
An open, Interactive 3D Design Collaboration Platform for Multi-Tool Workflows to simplify studio workflows for real-time graphics.
It supports Pixar’s Universal Scene Description technology for exchanging information about modeling, shading, animation, lighting, visual effects and rendering across multiple applications.
It also supports NVIDIA’s Material Definition Language, which allows artists to exchange information about surface materials across multiple tools.
With Omniverse, artists can see live updates made by other artists working in different applications. They can also see changes reflected in multiple tools at the same time.
For example an artist using Maya with a portal to Omniverse can collaborate with another artist using UE4 and both will see live updates of each others’ changes in their application.
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Unity 3D resources
http://answers.unity3d.com/questions/12321/how-can-i-start-learning-unity-fast-list-of-tutori.html
If you have no previous experience with Unity, start with these six video tutorials which give a quick overview of the Unity interface and some important features http://unity3d.com/support/documentation/video/
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DiffusionLight: HDRI Light Probes for Free by Painting a Chrome Ball
Read more: DiffusionLight: HDRI Light Probes for Free by Painting a Chrome Ballhttps://diffusionlight.github.io/
https://github.com/DiffusionLight/DiffusionLight
https://github.com/DiffusionLight/DiffusionLight?tab=MIT-1-ov-file#readme
https://colab.research.google.com/drive/15pC4qb9mEtRYsW3utXkk-jnaeVxUy-0S
“a simple yet effective technique to estimate lighting in a single input image. Current techniques rely heavily on HDR panorama datasets to train neural networks to regress an input with limited field-of-view to a full environment map. However, these approaches often struggle with real-world, uncontrolled settings due to the limited diversity and size of their datasets. To address this problem, we leverage diffusion models trained on billions of standard images to render a chrome ball into the input image. Despite its simplicity, this task remains challenging: the diffusion models often insert incorrect or inconsistent objects and cannot readily generate images in HDR format. Our research uncovers a surprising relationship between the appearance of chrome balls and the initial diffusion noise map, which we utilize to consistently generate high-quality chrome balls. We further fine-tune an LDR difusion model (Stable Diffusion XL) with LoRA, enabling it to perform exposure bracketing for HDR light estimation. Our method produces convincing light estimates across diverse settings and demonstrates superior generalization to in-the-wild scenarios.”
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NVidia DiffusionRenderer – Neural Inverse and Forward Rendering with Video Diffusion Models. How NVIDIA reimagined relighting
https://www.fxguide.com/quicktakes/diffusing-reality-how-nvidia-reimagined-relighting/
https://research.nvidia.com/labs/toronto-ai/DiffusionRenderer/
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Composition – cinematography Cheat Sheet
Where is our eye attracted first? Why?
Size. Focus. Lighting. Color.
Size. Mr. White (Harvey Keitel) on the right.
Focus. He’s one of the two objects in focus.
Lighting. Mr. White is large and in focus and Mr. Pink (Steve Buscemi) is highlighted by
a shaft of light.
Color. Both are black and white but the read on Mr. White’s shirt now really stands out.
What type of lighting?-> High key lighting.
Features bright, even illumination and few conspicuous shadows. This lighting key is often used in musicals and comedies.Low key lighting
Features diffused shadows and atmospheric pools of light. This lighting key is often used in mysteries and thrillers.High contrast lighting
Features harsh shafts of lights and dramatic streaks of blackness. This type of lighting is often used in tragedies and melodramas.What type of shot?
Extreme long shot
Taken from a great distance, showing much of the locale. Ifpeople are included in these shots, they usually appear as mere specks-> Long shot
Corresponds to the space between the audience and the stage in a live theater. The long shots show the characters and some of the locale.Full shot
Range with just enough space to contain the human body in full. The full shot shows the character and a minimal amount of the locale.Medium shot
Shows the human figure from the knees or waist up.Close-Up
Concentrates on a relatively small object and show very little if any locale.Extreme close-up
Focuses on an unnaturally small portion of an object, giving that part great detail and symbolic significance.What angle?
Bird’s-eye view.
The shot is photographed directly from above. This type of shot can be disorienting, and the people photographed seem insignificant.High angle.
This angle reduces the size of the objects photographed. A person photographed from this angle seems harmless and insignificant, but to a lesser extent than with the bird’s-eye view.-> Eye-level shot.
The clearest view of an object, but seldom intrinsically dramatic, because it tends to be the norm.Low angle.
This angle increases high and a sense of verticality, heightening the importance of the object photographed. A person shot from this angle is given a sense of power and respect.Oblique angle.
For this angle, the camera is tilted laterally, giving the image a slanted appearance. Oblique angles suggest tension, transition, a impending movement. They are also called canted or dutch angles.What is the dominant color?
The use of color in this shot is symbolic. The scene is set in warehouse. Both the set and characters are blues, blacks and whites.
This was intentional allowing for the scenes and shots with blood to have a great level of contrast.
What is the Lens/Filter/Stock?
Telephoto lens.
A lens that draws objects closer but also diminishes the illusion of depth.Wide-angle lens.
A lens that takes in a broad area and increases the illusion of depth but sometimes distorts the edges of the image.Fast film stock.
Highly sensitive to light, it can register an image with little illumination. However, the final product tends to be grainy.Slow film stock.
Relatively insensitive to light, it requires a great deal of illumination. The final product tends to look polished.The lens is not wide-angle because there isn’t a great sense of depth, nor are several planes in focus. The lens is probably long but not necessarily a telephoto lens because the depth isn’t inordinately compressed.
The stock is fast because of the grainy quality of the image.
Subsidiary Contrast; where does the eye go next?
The two guns.
How much visual information is packed into the image? Is the texture stark, moderate, or highly detailed?
Minimalist clutter in the warehouse allows a focus on a character driven thriller.
What is the Composition?
Horizontal.
Compositions based on horizontal lines seem visually at rest and suggest placidity or peacefulness.Vertical.
Compositions based on vertical lines seem visually at rest and suggest strength.-> Diagonal.
Compositions based on diagonal, or oblique, lines seem dynamic and suggest tension or anxiety.-> Binary. Binary structures emphasize parallelism.
Triangle.
Triadic compositions stress the dynamic interplay among three mainCircle.
Circular compositions suggest security and enclosure.Is the form open or closed? Does the image suggest a window that arbitrarily isolates a fragment of the scene? Or a proscenium arch, in which the visual elements are carefully arranged and held in balance?
The most nebulous of all the categories of mise en scene, the type of form is determined by how consciously structured the mise en scene is. Open forms stress apparently simple techniques, because with these unself-conscious methods the filmmaker is able to emphasize the immediate, the familiar, the intimate aspects of reality. In open-form images, the frame tends to be deemphasized. In closed form images, all the necessary information is carefully structured within the confines of the frame. Space seems enclosed and self-contained rather than continuous.
Could argue this is a proscenium arch because this is such a classic shot with parallels and juxtapositions.
Is the framing tight or loose? Do the character have no room to move around, or can they move freely without impediments?
Shots where the characters are placed at the edges of the frame and have little room to move around within the frame are considered tight.
Longer shots, in which characters have room to move around within the frame, are considered loose and tend to suggest freedom.
Center-framed giving us the entire scene showing isolation, place and struggle.
Depth of Field. On how many planes is the image composed (how many are in focus)? Does the background or foreground comment in any way on the mid-ground?
Standard DOF, one background and clearly defined foreground.
Which way do the characters look vis-a-vis the camera?
An actor can be photographed in any of five basic positions, each conveying different psychological overtones.
Full-front (facing the camera):
the position with the most intimacy. The character is looking in our direction, inviting our complicity.Quarter Turn:
the favored position of most filmmakers. This position offers a high degree of intimacy but with less emotional involvement than the full-front.-> Profile (looking of the frame left or right):
More remote than the quarter turn, the character in profile seems unaware of being observed, lost in his or her own thoughts.Three-quarter Turn:
More anonymous than the profile, this position is useful for conveying a character’s unfriendly or antisocial feelings, for in effect, the character is partially turning his or her back on us, rejecting our interest.Back to Camera:
The most anonymous of all positions, this position is often used to suggest a character’s alienation from the world. When a character has his or her back to the camera, we can only guess what’s taking place internally, conveying a sense of concealment, or mystery.How much space is there between the characters?
Extremely close, for a gunfight.
The way people use space can be divided into four proxemic patterns.
Intimate distances.
The intimate distance ranges from skin contact to about eighteen inches away. This is the distance of physical involvement–of love, comfort, and tenderness between individuals.-> Personal distances.
The personal distance ranges roughly from eighteen inches away to about four feet away. These distances tend to be reserved for friends and acquaintances. Personal distances preserve the privacy between individuals, yet these rages don’t necessarily suggest exclusion, as intimate distances often do.Social distances.
The social distance rages from four feet to about twelve feet. These distances are usually reserved for impersonal business and casual social gatherings. It’s a friendly range in most cases, yet somewhat more formal than the personal distance.Public distances.
The public distance extends from twelve feet to twenty-five feet or more. This range tends to be formal and rather detached. -
Aputure AL-F7 – dimmable Led Video Light, CRI95+, 3200-9500K
High CRI of ≥95
256 LEDs with 45° beam angle
3200 to 9500K variable color temperature
1 to 100% Stepless Dimming, 1500 Lux Brightness at 3.3′
LCD Info Screen. Powered by an L-series battery, D-Tap, or USB-C
Because the light has a variable color range of 3200 to 9500K, when the light is set to 5500K (daylight balanced) both sets of LEDs are on at full, providing the maximum brightness from this fixture when compared to using the light at 3200 or 9500K.
The LCD screen provides information on the fixture’s output as well as the charge state of the battery. The screen also indicates whether the adjustment knob is controlling brightness or color temperature. To switch from brightness to CCT or CCT to brightness, just apply a short press to the adjustment knob.
The included cold shoe ball joint adapter enables mounting the light to your camera’s accessory shoe via the 1/4″-20 threaded hole on the fixture. In addition, the bottom of the cold shoe foot features a 3/8″-16 threaded hole, and includes a 3/8″-16 to 1/4″-20 reducing bushing.
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