COMPOSITION
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StudioBinder – Roger Deakins on How to Choose a Camera Lens — Cinematography Composition Techniques
Read more: StudioBinder – Roger Deakins on How to Choose a Camera Lens — Cinematography Composition Techniques
https://www.studiobinder.com/blog/camera-lens-buying-guide/
https://www.studiobinder.com/blog/e-books/camera-lenses-explained-volume-1-ebook
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SlowMoVideo – How to make a slow motion shot with the open source program
Read more: SlowMoVideo – How to make a slow motion shot with the open source programhttp://slowmovideo.granjow.net/
slowmoVideo is an OpenSource program that creates slow-motion videos from your footage.
Slow motion cinematography is the result of playing back frames for a longer duration than they were exposed. For example, if you expose 240 frames of film in one second, then play them back at 24 fps, the resulting movie is 10 times longer (slower) than the original filmed event….
Film cameras are relatively simple mechanical devices that allow you to crank up the speed to whatever rate the shutter and pull-down mechanism allow. Some film cameras can operate at 2,500 fps or higher (although film shot in these cameras often needs some readjustment in postproduction). Video, on the other hand, is always captured, recorded, and played back at a fixed rate, with a current limit around 60fps. This makes extreme slow motion effects harder to achieve (and less elegant) on video, because slowing down the video results in each frame held still on the screen for a long time, whereas with high-frame-rate film there are plenty of frames to fill the longer durations of time. On video, the slow motion effect is more like a slide show than smooth, continuous motion.
One obvious solution is to shoot film at high speed, then transfer it to video (a case where film still has a clear advantage, sorry George). Another possibility is to cross dissolve or blur from one frame to the next. This adds a smooth transition from one still frame to the next. The blur reduces the sharpness of the image, and compared to slowing down images shot at a high frame rate, this is somewhat of a cheat. However, there isn’t much you can do about it until video can be recorded at much higher rates. Of course, many film cameras can’t shoot at high frame rates either, so the whole super-slow-motion endeavor is somewhat specialized no matter what medium you are using. (There are some high speed digital cameras available now that allow you to capture lots of digital frames directly to your computer, so technology is starting to catch up with film. However, this feature isn’t going to appear in consumer camcorders any time soon.)
DESIGN
COLOR
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Practical Aspects of Spectral Data and LEDs in Digital Content Production and Virtual Production – SIGGRAPH 2022
Read more: Practical Aspects of Spectral Data and LEDs in Digital Content Production and Virtual Production – SIGGRAPH 2022
Comparison to the commercial side
https://www.ecolorled.com/blog/detail/what-is-rgb-rgbw-rgbic-strip-lights
RGBW (RGB + White) LED strip uses a 4-in-1 LED chip made up of red, green, blue, and white.
RGBWW (RGB + White + Warm White) LED strip uses either a 5-in-1 LED chip with red, green, blue, white, and warm white for color mixing. The only difference between RGBW and RGBWW is the intensity of the white color. The term RGBCCT consists of RGB and CCT. CCT (Correlated Color Temperature) means that the color temperature of the led strip light can be adjusted to change between warm white and white. Thus, RGBWW strip light is another name of RGBCCT strip.
RGBCW is the acronym for Red, Green, Blue, Cold, and Warm. These 5-in-1 chips are used in supper bright smart LED lighting products
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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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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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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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Willem Zwarthoed – Aces gamut in VFX production pdf
Read more: Willem Zwarthoed – Aces gamut in VFX production pdfhttps://www.provideocoalition.com/color-management-part-12-introducing-aces/
Local copy:
https://www.slideshare.net/hpduiker/acescg-a-common-color-encoding-for-visual-effects-applications
![[gamma correction test]](http://www.madore.org/~david/misc/color/gammatest.png "sRGB gamma correction test")
LIGHTING
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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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domeble – Hi-Resolution CGI Backplates and 360° HDRI
Read more: domeble – Hi-Resolution CGI Backplates and 360° HDRIWhen collecting hdri make sure the data supports basic metadata, such as:
- Iso
- Aperture
- Exposure time or shutter time
- Color temperature
- Color space Exposure value (what the sensor receives of the sun intensity in lux)
- 7+ brackets (with 5 or 6 being the perceived balanced exposure)
In image processing, computer graphics, and photography, high dynamic range imaging (HDRI or just HDR) is a set of techniques that allow a greater dynamic range of luminances (a Photometry measure of the luminous intensity per unit area of light travelling in a given direction. It describes the amount of light that passes through or is emitted from a particular area, and falls within a given solid angle) between the lightest and darkest areas of an image than standard digital imaging techniques or photographic methods. This wider dynamic range allows HDR images to represent more accurately the wide range of intensity levels found in real scenes ranging from direct sunlight to faint starlight and to the deepest shadows.
The two main sources of HDR imagery are computer renderings and merging of multiple photographs, which in turn are known as low dynamic range (LDR) or standard dynamic range (SDR) images. Tone Mapping (Look-up) techniques, which reduce overall contrast to facilitate display of HDR images on devices with lower dynamic range, can be applied to produce images with preserved or exaggerated local contrast for artistic effect. Photography
In photography, dynamic range is measured in Exposure Values (in photography, exposure value denotes all combinations of camera shutter speed and relative aperture that give the same exposure. The concept was developed in Germany in the 1950s) differences or stops, between the brightest and darkest parts of the image that show detail. An increase of one EV or one stop is a doubling of the amount of light.
The human response to brightness is well approximated by a Steven’s power law, which over a reasonable range is close to logarithmic, as described by the Weber�Fechner law, which is one reason that logarithmic measures of light intensity are often used as well.
HDR is short for High Dynamic Range. It’s a term used to describe an image which contains a greater exposure range than the “black” to “white” that 8 or 16-bit integer formats (JPEG, TIFF, PNG) can describe. Whereas these Low Dynamic Range images (LDR) can hold perhaps 8 to 10 f-stops of image information, HDR images can describe beyond 30 stops and stored in 32 bit images.
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