COMPOSITION
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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/
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Christopher Butler – Understanding the Eye-Mind Connection – Vision is a mental process
Read more: Christopher Butler – Understanding the Eye-Mind Connection – Vision is a mental processhttps://www.chrbutler.com/understanding-the-eye-mind-connection
The intricate relationship between the eyes and the brain, often termed the eye-mind connection, reveals that vision is predominantly a cognitive process. This understanding has profound implications for fields such as design, where capturing and maintaining attention is paramount. This essay delves into the nuances of visual perception, the brain’s role in interpreting visual data, and how this knowledge can be applied to effective design strategies.
This cognitive aspect of vision is evident in phenomena such as optical illusions, where the brain interprets visual information in a way that contradicts physical reality. These illusions underscore that what we “see” is not merely a direct recording of the external world but a constructed experience shaped by cognitive processes.
Understanding the cognitive nature of vision is crucial for effective design. Designers must consider how the brain processes visual information to create compelling and engaging visuals. This involves several key principles:
- Attention and Engagement
- Visual Hierarchy
- Cognitive Load Management
- Context and Meaning
DESIGN
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boldtron – 𝗗𝗘𝗣𝗜𝗖𝗧𝗜𝗡𝗚 𝗪𝗔𝗧𝗘𝗥𝗚𝗨𝗡𝗦
Read more: boldtron – 𝗗𝗘𝗣𝗜𝗖𝗧𝗜𝗡𝗚 𝗪𝗔𝗧𝗘𝗥𝗚𝗨𝗡𝗦See this Instagram post by @boldtron using ComfyUI + Krea
https://www.instagram.com/p/C5v-H0PNYYg/?utm_source=ig_web_button_share_sheet
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Kristina Kashtanova – “This is how GPT-4 sees and hears itself”
“I used GPT-4 to describe itself. Then I used its description to generate an image, a video based on this image and a soundtrack.
Tools I used: GPT-4, Midjourney, Kaiber AI, Mubert, RunwayML
This is the description I used that GPT-4 had of itself as a prompt to text-to-image, image-to-video, and text-to-music. I put the video and sound together in RunwayML.
GPT-4 described itself as: “Imagine a sleek, metallic sphere with a smooth surface, representing the vast knowledge contained within the model. The sphere emits a soft, pulsating glow that shifts between various colors, symbolizing the dynamic nature of the AI as it processes information and generates responses. The sphere appears to float in a digital environment, surrounded by streams of data and code, reflecting the complex algorithms and computing power behind the AI”
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Tokyo Prime 1 Studio 2022 + XM Studios Boots | Batman, Movies, Anime & Games Statues and Collectibles
Read more: Tokyo Prime 1 Studio 2022 + XM Studios Boots | Batman, Movies, Anime & Games Statues and Collectiblesnearly 140 statues at the booth from licenses including DC Comics, Lord of the Rings, Uncharted, The Last of Us, Bloodborne, Demon Souls, God of War, Jurassic Park, Godzilla, Predator, Aliens, Transformers, Berserk, Evangelion, My Hero Academia, Chainsaw Man, Attack on Titan, the DC movie universe, X-Men, Spider-man and much more
COLOR
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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.
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Christopher Butler – Understanding the Eye-Mind Connection – Vision is a mental process
Read more: Christopher Butler – Understanding the Eye-Mind Connection – Vision is a mental processhttps://www.chrbutler.com/understanding-the-eye-mind-connection
The intricate relationship between the eyes and the brain, often termed the eye-mind connection, reveals that vision is predominantly a cognitive process. This understanding has profound implications for fields such as design, where capturing and maintaining attention is paramount. This essay delves into the nuances of visual perception, the brain’s role in interpreting visual data, and how this knowledge can be applied to effective design strategies.
This cognitive aspect of vision is evident in phenomena such as optical illusions, where the brain interprets visual information in a way that contradicts physical reality. These illusions underscore that what we “see” is not merely a direct recording of the external world but a constructed experience shaped by cognitive processes.
Understanding the cognitive nature of vision is crucial for effective design. Designers must consider how the brain processes visual information to create compelling and engaging visuals. This involves several key principles:
- Attention and Engagement
- Visual Hierarchy
- Cognitive Load Management
- Context and Meaning
LIGHTING
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Photography basics: How Exposure Stops (Aperture, Shutter Speed, and ISO) Affect Your Photos – cheat sheet cards
Also see:
https://www.pixelsham.com/2018/11/22/exposure-value-measurements/
https://www.pixelsham.com/2016/03/03/f-stop-vs-t-stop/
An exposure stop is a unit measurement of Exposure as such it provides a universal linear scale to measure the increase and decrease in light, exposed to the image sensor, due to changes in shutter speed, iso and f-stop.
+-1 stop is a doubling or halving of the amount of light let in when taking a photo
1 EV (exposure value) is just another way to say one stop of exposure change.
https://www.photographymad.com/pages/view/what-is-a-stop-of-exposure-in-photography
Same applies to shutter speed, iso and aperture.
Doubling or halving your shutter speed produces an increase or decrease of 1 stop of exposure.
Doubling or halving your iso speed produces an increase or decrease of 1 stop of exposure.Because of the way f-stop numbers are calculated (ratio of focal length/lens diameter, where focal length is the distance between the lens and the sensor), an f-stop doesn’t relate to a doubling or halving of the value, but to the doubling/halving of the area coverage of a lens in relation to its focal length. And as such, to a multiplying or dividing by 1.41 (the square root of 2). For example, going from f/2.8 to f/4 is a decrease of 1 stop because 4 = 2.8 * 1.41. Changing from f/16 to f/11 is an increase of 1 stop because 11 = 16 / 1.41.
A wider aperture means that light proceeding from the foreground, subject, and background is entering at more oblique angles than the light entering less obliquely.
Consider that absolutely everything is bathed in light, therefore light bouncing off of anything is effectively omnidirectional. Your camera happens to be picking up a tiny portion of the light that’s bouncing off into infinity.
Now consider that the wider your iris/aperture, the more of that omnidirectional light you’re picking up:
When you have a very narrow iris you are eliminating a lot of oblique light. Whatever light enters, from whatever distance, enters moderately parallel as a whole. When you have a wide aperture, much more light is entering at a multitude of angles. Your lens can only focus the light from one depth – the foreground/background appear blurred because it cannot be focused on.
https://frankwhitephotography.com/index.php?id=28:what-is-a-stop-in-photography
The great thing about stops is that they give us a way to directly compare shutter speed, aperture diameter, and ISO speed. This means that we can easily swap these three components about while keeping the overall exposure the same.
http://lifehacker.com/how-aperture-shutter-speed-and-iso-affect-pictures-sh-1699204484
https://www.techradar.com/how-to/the-exposure-triangle
https://www.videoschoolonline.com/what-is-an-exposure-stop
Note. All three of these measurements (aperture, shutter, iso) have full stops, half stops and third stops, but if you look at the numbers they aren’t always consistent. For example, a one third stop between ISO100 and ISO 200 would be ISO133, yet most cameras are marked at ISO125.
Third-stops are especially important as they’re the increment that most cameras use for their settings. These are just imaginary divisions in each stop.
From a practical standpoint manufacturers only standardize the full stops, meaning that while they try and stay somewhat consistent there is some rounding up going on between the smaller numbers.Note that ND Filters directly modify the exposure triangle.
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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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Key/Fill ratios and scene composition using false colors
To measure the contrast ratio you will need a light meter. The process starts with you measuring the main source of light, or the key light.
Get a reading from the brightest area on the face of your subject. Then, measure the area lit by the secondary light, or fill light. To make sense of what you have just measured you have to understand that the information you have just gathered is in F-stops, a measure of light. With each additional F-stop, for example going one stop from f/1.4 to f/2.0, you create a doubling of light. The reverse is also true; moving one stop from f/8.0 to f/5.6 results in a halving of the light.
Let’s say you grabbed a measurement from your key light of f/8.0. Then, when you measured your fill light area, you get a reading of f/4.0. This will lead you to a contrast ratio of 4:1 because there are two stops between f/4.0 and f/8.0 and each stop doubles the amount of light. In other words, two stops x twice the light per stop = four times as much light at f/8.0 than at f/4.0.
theslantedlens.com/2017/lighting-ratios-photo-video/
Examples in the post
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Arto T. – A workflow for creating photorealistic, equirectangular 360° panoramas in ComfyUI using Flux
https://civitai.com/models/735980/flux-equirectangular-360-panorama
https://civitai.com/models/745010?modelVersionId=833115
The trigger phrase is “equirectangular 360 degree panorama”. I would avoid saying “spherical projection” since that tends to result in non-equirectangular spherical images.
Image resolution should always be a 2:1 aspect ratio. 1024 x 512 or 1408 x 704 work quite well and were used in the training data. 2048 x 1024 also works.
I suggest using a weight of 0.5 – 1.5. If you are having issues with the image generating too flat instead of having the necessary spherical distortion, try increasing the weight above 1, though this could negatively impact small details of the image. For Flux guidance, I recommend a value of about 2.5 for realistic scenes.
8-bit output at the moment
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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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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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