COMPOSITION
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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
  
DESIGN
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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Space bodies’ components and light spectroscopyRead more: Space bodies’ components and light spectroscopywww.plutorules.com/page-111-space-rocks.html This help’s us understand the composition of components in/on solar system bodies. Dips in the observed light spectrum, also known as, lines of absorption occur as gasses absorb energy from light at specific points along the light spectrum. These dips or darkened zones (lines of absorption) leave a finger print which identify elements and compounds. In this image the dark absorption bands appear as lines of emission which occur as the result of emitted not reflected (absorbed) light. Lines of absorption  Lines of emission Lines of emission    
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Victor Perez – ACES Color Management in DaVinci ResolveRead more: Victor Perez – ACES Color Management in DaVinci Resolvehttpv://www.youtube.com/watch?v=i–TS88-6xA 
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If a blind person gained sight, could they recognize objects previously touched?Read more: 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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THOMAS MANSENCAL – The Apparent Simplicity of RGB RenderingRead more: THOMAS MANSENCAL – The Apparent Simplicity of RGB Renderinghttps://thomasmansencal.substack.com/p/the-apparent-simplicity-of-rgb-rendering The primary goal of physically-based rendering (PBR) is to create a simulation that accurately reproduces the imaging process of electro-magnetic spectrum radiation incident to an observer. This simulation should be indistinguishable from reality for a similar observer. Because a camera is not sensitive to incident light the same way than a human observer, the images it captures are transformed to be colorimetric. A project might require infrared imaging simulation, a portion of the electro-magnetic spectrum that is invisible to us. Radically different observers might image the same scene but the act of observing does not change the intrinsic properties of the objects being imaged. Consequently, the physical modelling of the virtual scene should be independent of the observer. 
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Björn Ottosson – How software gets color wrongRead 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: 
LIGHTING
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Capturing the world in HDR for real time projects – Call of Duty: Advanced WarfareRead more: Capturing the world in HDR for real time projects – Call of Duty: Advanced WarfareReal-World Measurements for Call of Duty: Advanced Warfare www.activision.com/cdn/research/Real_World_Measurements_for_Call_of_Duty_Advanced_Warfare.pdf Local version Real_World_Measurements_for_Call_of_Duty_Advanced_Warfare.pdf 
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Simulon – a Hollywood production studio app in the hands of an independent creator with access to consumer hardware, LDRi to HDRi through MLRead more: Simulon – a Hollywood production studio app in the hands of an independent creator with access to consumer hardware, LDRi to HDRi through MLDivesh Naidoo: The video below was made with a live in-camera preview and auto-exposure matching, no camera solve, no HDRI capture and no manual compositing setup. Using the new Simulon phone app. LDR to HDR through ML https://simulon.typeform.com/betatest (more…)Process example 
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Vahan Sosoyan MakeHDR – an OpenFX open source plug-in for merging multiple LDR images into a single HDRIRead 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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HDRI shooting and editing by Xuan Prada and Greg ZaalRead more: HDRI shooting and editing by Xuan Prada and Greg Zaalwww.xuanprada.com/blog/2014/11/3/hdri-shooting http://blog.gregzaal.com/2016/03/16/make-your-own-hdri/ http://blog.hdrihaven.com/how-to-create-high-quality-hdri/  Shooting checklist - Full coverage of the scene (fish-eye shots)
- Backplates for look-development (including ground or floor)
- Macbeth chart for white balance
- Grey ball for lighting calibration
- Chrome ball for lighting orientation
- Basic scene measurements
- Material samples
- Individual HDR artificial lighting sources if required
 Methodology (more…)
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