COMPOSITION
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Photography basics: Depth of Field and composition
Read more: Photography basics: Depth of Field and compositionDepth of field is the range within which focusing is resolved in a photo.
Aperture has a huge affect on to the depth of field.Changing the f-stops (f/#) of a lens will change aperture and as such the DOF.
f-stops are a just certain number which is telling you the size of the aperture. That’s how f-stop is related to aperture (and DOF).
If you increase f-stops, it will increase DOF, the area in focus (and decrease the aperture). On the other hand, decreasing the f-stop it will decrease DOF (and increase the aperture).
The red cone in the figure is an angular representation of the resolution of the system. Versus the dotted lines, which indicate the aperture coverage. Where the lines of the two cones intersect defines the total range of the depth of field.
This image explains why the longer the depth of field, the greater the range of clarity.
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Photography basics: Camera Aspect Ratio, Sensor Size and Depth of Field – resolutions
http://www.shutterangle.com/2012/cinematic-look-aspect-ratio-sensor-size-depth-of-field/
http://www.shutterangle.com/2012/film-video-aspect-ratio-artistic-choice/
DESIGN
COLOR
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Willem Zwarthoed – Aces gamut in VFX production pdf
https://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
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Scene Referred vs Display Referred color workflows
Read more: Scene Referred vs Display Referred color workflowsDisplay Referred it is tied to the target hardware, as such it bakes color requirements into every type of media output request.
Scene Referred uses a common unified wide gamut and targeting audience through CDL and DI libraries instead.
So that color information stays untouched and only “transformed” as/when needed.Sources:
– Victor Perez – Color Management Fundamentals & ACES Workflows in Nuke
– https://z-fx.nl/ColorspACES.pdf
– Wicus
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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/
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Weta Digital – Manuka Raytracer and Gazebo GPU renderers – pipeline
Read more: Weta Digital – Manuka Raytracer and Gazebo GPU renderers – pipelinehttps://jo.dreggn.org/home/2018_manuka.pdf
http://www.fxguide.com/featured/manuka-weta-digitals-new-renderer/
The Manuka rendering architecture has been designed in the spirit of the classic reyes rendering architecture. In its core, reyes is based on stochastic rasterisation of micropolygons, facilitating depth of field, motion blur, high geometric complexity,and programmable shading.
This is commonly achieved with Monte Carlo path tracing, using a paradigm often called shade-on-hit, in which the renderer alternates tracing rays with running shaders on the various ray hits. The shaders take the role of generating the inputs of the local material structure which is then used bypath sampling logic to evaluate contributions and to inform what further rays to cast through the scene.
Over the years, however, the expectations have risen substantially when it comes to image quality. Computing pictures which are indistinguishable from real footage requires accurate simulation of light transport, which is most often performed using some variant of Monte Carlo path tracing. Unfortunately this paradigm requires random memory accesses to the whole scene and does not lend itself well to a rasterisation approach at all.
Manuka is both a uni-directional and bidirectional path tracer and encompasses multiple importance sampling (MIS). Interestingly, and importantly for production character skin work, it is the first major production renderer to incorporate spectral MIS in the form of a new ‘Hero Spectral Sampling’ technique, which was recently published at Eurographics Symposium on Rendering 2014.
Manuka propose a shade-before-hit paradigm in-stead and minimise I/O strain (and some memory costs) on the system, leveraging locality of reference by running pattern generation shaders before we execute light transport simulation by path sampling, “compressing” any bvh structure as needed, and as such also limiting duplication of source data.
The difference with reyes is that instead of baking colors into the geometry like in Reyes, manuka bakes surface closures. This means that light transport is still calculated with path tracing, but all texture lookups etc. are done up-front and baked into the geometry.The main drawback with this method is that geometry has to be tessellated to its highest, stable topology before shading can be evaluated properly. As such, the high cost to first pixel. Even a basic 4 vertices square becomes a much more complex model with this approach.
Manuka use the RenderMan Shading Language (rsl) for programmable shading [Pixar Animation Studios 2015], but we do not invoke rsl shaders when intersecting a ray with a surface (often called shade-on-hit). Instead, we pre-tessellate and pre-shade all the input geometry in the front end of the renderer.
This way, we can efficiently order shading computations to sup-port near-optimal texture locality, vectorisation, and parallelism. This system avoids repeated evaluation of shaders at the same surface point, and presents a minimal amount of memory to be accessed during light transport time. An added benefit is that the acceleration structure for ray tracing (abounding volume hierarchy, bvh) is built once on the final tessellated geometry, which allows us to ray trace more efficiently than multi-level bvhs and avoids costly caching of on-demand tessellated micropolygons and the associated scheduling issues.For the shading reasons above, in terms of AOVs, the studio approach is to succeed at combining complex shading with ray paths in the render rather than pass a multi-pass render to compositing.
For the Spectral Rendering component. The light transport stage is fully spectral, using a continuously sampled wavelength which is traced with each path and used to apply the spectral camera sensitivity of the sensor. This allows for faithfully support any degree of observer metamerism as the camera footage they are intended to match as well as complex materials which require wavelength dependent phenomena such as diffraction, dispersion, interference, iridescence, or chromatic extinction and Rayleigh scattering in participating media.
As opposed to the original reyes paper, we use bilinear interpolation of these bsdf inputs later when evaluating bsdfs per pathv ertex during light transport4. This improves temporal stability of geometry which moves very slowly with respect to the pixel raster
In terms of the pipeline, everything rendered at Weta was already completely interwoven with their deep data pipeline. Manuka very much was written with deep data in mind. Here, Manuka not so much extends the deep capabilities, rather it fully matches the already extremely complex and powerful setup Weta Digital already enjoy with RenderMan. For example, an ape in a scene can be selected, its ID is available and a NUKE artist can then paint in 3D say a hand and part of the way up the neutral posed ape.
We called our system Manuka, as a respectful nod to reyes: we had heard a story froma former ILM employee about how reyes got its name from how fond the early Pixar people were of their lunches at Point Reyes, and decided to name our system after our surrounding natural environment, too. Manuka is a kind of tea tree very common in New Zealand which has very many very small leaves, in analogy to micropolygons ina tree structure for ray tracing. It also happens to be the case that Weta Digital’s main site is on Manuka Street.
LIGHTING
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Fast, optimized ‘for’ pixel loops with OpenCV and Python to create tone mapped HDR images
Read more: Fast, optimized ‘for’ pixel loops with OpenCV and Python to create tone mapped HDR imageshttps://pyimagesearch.com/2017/08/28/fast-optimized-for-pixel-loops-with-opencv-and-python/
https://learnopencv.com/exposure-fusion-using-opencv-cpp-python/
Exposure Fusion is a method for combining images taken with different exposure settings into one image that looks like a tone mapped High Dynamic Range (HDR) image.
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Vahan Sosoyan MakeHDR – an OpenFX open source plug-in for merging multiple LDR images into a single HDRI
Read more: Vahan Sosoyan MakeHDR – an OpenFX open source plug-in for merging multiple LDR images into a single HDRIhttps://github.com/Sosoyan/make-hdr
Feature notes
- Merge up to 16 inputs with 8, 10 or 12 bit depth processing
- User friendly logarithmic Tone Mapping controls within the tool
- Advanced controls such as Sampling rate and Smoothness
Available at cross platform on Linux, MacOS and Windows Works consistent in compositing applications like Nuke, Fusion, Natron.
NOTE: The goal is to clean the initial individual brackets before or at merging time as much as possible.
This means:- keeping original shooting metadata
- de-fringing
- removing aberration (through camera lens data or automatically)
- at 32 bit
- in ACEScg (or ACES) wherever possible
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Composition and The Expressive Nature Of Light
Read more: Composition and The Expressive Nature Of Lighthttp://www.huffingtonpost.com/bill-danskin/post_12457_b_10777222.html
George Sand once said “ The artist vocation is to send light into the human heart.”
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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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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 2022Comparison 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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FEATURED POSTS
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Photography basics: How Exposure Stops (Aperture, Shutter Speed, and ISO) Affect Your Photos – cheat sheet cards
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Glossary of Lighting Terms – cheat sheet
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Principles of Animation with Alan Becker, Dermot OConnor and Shaun Keenan
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Sensitivity of human eye
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Image rendering bit depth
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Photography basics: Solid Angle measures
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