COMPOSITION
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Composition – These are the basic lighting techniques you need to know for photography and filmRead more: Composition – These are the basic lighting techniques you need to know for photography and filmhttp://www.diyphotography.net/basic-lighting-techniques-need-know-photography-film/ Amongst the basic techniques, there’s… 1- Side lighting – Literally how it sounds, lighting a subject from the side when they’re faced toward you 2- Rembrandt lighting – Here the light is at around 45 degrees over from the front of the subject, raised and pointing down at 45 degrees 3- Back lighting – Again, how it sounds, lighting a subject from behind. This can help to add drama with silouettes 4- Rim lighting – This produces a light glowing outline around your subject 5- Key light – The main light source, and it’s not necessarily always the brightest light source 6- Fill light – This is used to fill in the shadows and provide detail that would otherwise be blackness 7- Cross lighting – Using two lights placed opposite from each other to light two subjects 
DESIGN
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Mania Carta – Photorealistic Characters Made in BlenderRead more: Mania Carta – Photorealistic Characters Made in BlenderManiacarta is an Artist based in Tokyo, her Artworks are unique and she strive to create the best characters that have soul in the World. https://80.lv/articles/marvelous-photorealistic-characters-made-in-blender-by-mania-carta/ https://www.instagram.com/mania_carta/     
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How to paint a boardgame miniaturesRead more: How to paint a boardgame miniaturesSteps: - soap wash cleaning
- primer
- base-coat layer (black/white)
- detailing
- washing aka shade (could be done after highlighting)
- highlights aka dry brushing (could be done after washing)
- varnish (gloss/satin/matte)
 
COLOR
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Victor Perez – The Color Management Handbook for Visual Effects ArtistsRead more: Victor Perez – The Color Management Handbook for Visual Effects ArtistsDigital Color Principles, Color Management Fundamentals & ACES Workflows 
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Black Body color aka the Planckian Locus curve for white point eye perceptionRead more: Black Body color aka the Planckian Locus curve for white point eye perceptionhttp://en.wikipedia.org/wiki/Black-body_radiation  Black-body radiation is the type of electromagnetic radiation within or surrounding a body in thermodynamic equilibrium with its environment, or emitted by a black body (an opaque and non-reflective body) held at constant, uniform temperature. The radiation has a specific spectrum and intensity that depends only on the temperature of the body. A black-body at room temperature appears black, as most of the energy it radiates is infra-red and cannot be perceived by the human eye. At higher temperatures, black bodies glow with increasing intensity and colors that range from dull red to blindingly brilliant blue-white as the temperature increases. (more…)
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The Color of Infinite TemperatureRead more: The Color of Infinite TemperatureThis is the color of something infinitely hot.  Of course you’d instantly be fried by gamma rays of arbitrarily high frequency, but this would be its spectrum in the visible range. johncarlosbaez.wordpress.com/2022/01/16/the-color-of-infinite-temperature/ This is also the color of a typical neutron star. They’re so hot they look the same. 
 It’s also the color of the early Universe!This was worked out by David Madore.  The color he got is sRGB(148,177,255). 
 www.htmlcsscolor.com/hex/94B1FFAnd according to the experts who sip latte all day and make up names for colors, this color is called ‘Perano’. 
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Björn Ottosson – OKHSV and OKHSL – Two new color spaces for color pickingRead more: Björn Ottosson – OKHSV and OKHSL – Two new color spaces for color pickinghttps://bottosson.github.io/misc/colorpicker https://bottosson.github.io/posts/colorpicker/ https://www.smashingmagazine.com/2024/10/interview-bjorn-ottosson-creator-oklab-color-space/ One problem with sRGB is that in a gradient between blue and white, it becomes a bit purple in the middle of the transition. That’s because sRGB really isn’t created to mimic how the eye sees colors; rather, it is based on how CRT monitors work. That means it works with certain frequencies of red, green, and blue, and also the non-linear coding called gamma. It’s a miracle it works as well as it does, but it’s not connected to color perception. When using those tools, you sometimes get surprising results, like purple in the gradient. There were also attempts to create simple models matching human perception based on XYZ, but as it turned out, it’s not possible to model all color vision that way. Perception of color is incredibly complex and depends, among other things, on whether it is dark or light in the room and the background color it is against. When you look at a photograph, it also depends on what you think the color of the light source is. The dress is a typical example of color vision being very context-dependent. It is almost impossible to model this perfectly. I based Oklab on two other color spaces, CIECAM16 and IPT. I used the lightness and saturation prediction from CIECAM16, which is a color appearance model, as a target. I actually wanted to use the datasets used to create CIECAM16, but I couldn’t find them. IPT was designed to have better hue uniformity. In experiments, they asked people to match light and dark colors, saturated and unsaturated colors, which resulted in a dataset for which colors, subjectively, have the same hue. IPT has a few other issues but is the basis for hue in Oklab. In the Munsell color system, colors are described with three parameters, designed to match the perceived appearance of colors: Hue, Chroma and Value. The parameters are designed to be independent and each have a uniform scale. This results in a color solid with an irregular shape. The parameters are designed to be independent and each have a uniform scale. This results in a color solid with an irregular shape. Modern color spaces and models, such as CIELAB, Cam16 and Björn Ottosson own Oklab, are very similar in their construction.  By far the most used color spaces today for color picking are HSL and HSV, two representations introduced in the classic 1978 paper “Color Spaces for Computer Graphics”. HSL and HSV designed to roughly correlate with perceptual color properties while being very simple and cheap to compute. Today HSL and HSV are most commonly used together with the sRGB color space.  One of the main advantages of HSL and HSV over the different Lab color spaces is that they map the sRGB gamut to a cylinder. This makes them easy to use since all parameters can be changed independently, without the risk of creating colors outside of the target gamut.  The main drawback on the other hand is that their properties don’t match human perception particularly well. 
 Reconciling these conflicting goals perfectly isn’t possible, but given that HSV and HSL don’t use anything derived from experiments relating to human perception, creating something that makes a better tradeoff does not seem unreasonable. With this new lightness estimate, we are ready to look into the construction of Okhsv and Okhsl.  
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Weta Digital – Manuka Raytracer and Gazebo GPU renderers – pipelineRead 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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Christopher Butler – Understanding the Eye-Mind Connection – Vision is a mental processRead 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
  
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Types of Film Lights and their efficiency – CRI, Color Temperature and Luminous EfficacyRead more: Types of Film Lights and their efficiency – CRI, Color Temperature and Luminous Efficacynofilmschool.com/types-of-film-lights “Not every light performs the same way. Lights and lighting are tricky to handle. You have to plan for every circumstance. But the good news is, lighting can be adjusted. Let’s look at different factors that affect lighting in every scene you shoot. “ 
 Use CRI, Luminous Efficacy and color temperature controls to match your needs.Color Temperature 
 Color temperature describes the “color” of white light by a light source radiated by a perfect black body at a given temperature measured in degrees Kelvinhttps://www.pixelsham.com/2019/10/18/color-temperature/ CRI 
 “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. “https://www.studiobinder.com/blog/what-is-color-rendering-index (more…)
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GretagMacbeth Color Checker Numeric Values and Middle GrayRead 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 (more…)
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Arto T. – A workflow for creating photorealistic, equirectangular 360° panoramas in ComfyUI using FluxRead more: Arto T. – A workflow for creating photorealistic, equirectangular 360° panoramas in ComfyUI using Fluxhttps://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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Gamma correctionRead more: Gamma correction http://www.normankoren.com/makingfineprints1A.html#Gammabox https://en.wikipedia.org/wiki/Gamma_correction http://www.photoscientia.co.uk/Gamma.htm https://www.w3.org/Graphics/Color/sRGB.html http://www.eizoglobal.com/library/basics/lcd_display_gamma/index.html https://forum.reallusion.com/PrintTopic308094.aspx Basically, gamma is the relationship between the brightness of a pixel as it appears on the screen, and the numerical value of that pixel. Generally Gamma is just about defining relationships. Three main types: 
 – Image Gamma encoded in images
 – Display Gammas encoded in hardware and/or viewing time
 – System or Viewing Gamma which is the net effect of all gammas when you look back at a final image. In theory this should flatten back to 1.0 gamma.
 (more…)
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HDRI Median Cut pluginRead more: HDRI Median Cut pluginwww.hdrlabs.com/picturenaut/plugins.html  Note. The Median Cut algorithm is typically used for color quantization, which involves reducing the number of colors in an image while preserving its visual quality. It doesn’t directly provide a way to identify the brightest areas in an image. However, if you’re interested in identifying the brightest areas, you might want to look into other methods like thresholding, histogram analysis, or edge detection, through openCV for example. Here is an openCV example: (more…)
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