COMPOSITION
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Composition – cinematography Cheat SheetRead more: Composition – cinematography Cheat Sheet Where is our eye attracted first? Why? Size. Focus. Lighting. Color. Size. Mr. White (Harvey Keitel) on the right. 
 Focus. He’s one of the two objects in focus.
 Lighting. Mr. White is large and in focus and Mr. Pink (Steve Buscemi) is highlighted by
 a shaft of light.
 Color. Both are black and white but the read on Mr. White’s shirt now really stands out.
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 What type of lighting?
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7 Commandments of Film Editing and compositionRead more: 7 Commandments of Film Editing and composition1. Watch every frame of raw footage twice. On the second time, take notes. If you don’t do this and try to start developing a scene premature, then it’s a big disservice to yourself and to the director, actors and production crew. 2. Nurture the relationships with the director. You are the secondary person in the relationship. Be calm and continually offer solutions. Get the main intention of the film as soon as possible from the director. 3. Organize your media so that you can find any shot instantly. 4. Factor in extra time for renders, exports, errors and crashes. 5. Attempt edits and ideas that shouldn’t work. It just might work. Until you do it and watch it, you won’t know. Don’t rule out ideas just because they don’t make sense in your mind. 6. Spend more time on your audio. It’s the glue of your edit. AUDIO SAVES EVERYTHING. Create fluid and seamless audio under your video. 7. Make cuts for the scene, but always in context for the whole film. Have a macro and a micro view at all times. 
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Photography basics: Camera Aspect Ratio, Sensor Size and Depth of Field – resolutionsRead more: Photography basics: Camera Aspect Ratio, Sensor Size and Depth of Field – resolutionshttp://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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StudioBinder – Roger Deakins on How to Choose a Camera Lens — Cinematography Composition TechniquesRead more: StudioBinder – Roger Deakins on How to Choose a Camera Lens — Cinematography Composition Techniqueshttps://www.studiobinder.com/blog/camera-lens-buying-guide/ https://www.studiobinder.com/blog/e-books/camera-lenses-explained-volume-1-ebook 
DESIGN
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Kelly Boesch – Static and Toward The LightRead more: Kelly Boesch – Static and Toward The Lighthttps://www.kellyboeschdesign.com I was working an album cover last night and got these really cool images in midjourney so made a video out of it. Animated using Pika. Song made using Suno Full version on my bandcamp. It’s called Static. 
 https://www.linkedin.com/posts/kellyboesch_midjourney-keyframes-ai-activity-7359244714853736450-Wvcr(more…)
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This legendary DC Comics style guide was nearly lost for years – now you can buy itRead more: This legendary DC Comics style guide was nearly lost for years – now you can buy ithttps://www.fastcompany.com/91133306/dc-comics-style-guide-was-lost-for-years-now-you-can-buy-it Reproduced from a rare original copy, the book features over 165 highly-detailed scans of the legendary art by José Luis García-López, with an introduction by Paul Levitz, former president of DC Comics. https://standardsmanual.com/products/1982-dc-comics-style-guide 
COLOR
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Scene Referred vs Display Referred color workflowsRead 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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Scientists claim to have discovered ‘new colour’ no one has seen before: OloRead more: Scientists claim to have discovered ‘new colour’ no one has seen before: Olohttps://www.bbc.com/news/articles/clyq0n3em41o By stimulating specific cells in the retina, the participants claim to have witnessed a blue-green colour that scientists have called “olo”, but some experts have said the existence of a new colour is “open to argument”. The findings, published in the journal Science Advances on Friday, have been described by the study’s co-author, Prof Ren Ng from the University of California, as “remarkable”.  (A) System inputs. (i) Retina map of 103 cone cells preclassified by spectral type (7). (ii) Target visual percept (here, a video of a child, see movie S1 at 1:04). (iii) Infrared cellular-scale imaging of the retina with 60-frames-per-second rolling shutter. Fixational eye movement is visible over the three frames shown. (B) System outputs. (iv) Real-time per-cone target activation levels to reproduce the target percept, computed by: extracting eye motion from the input video relative to the retina map; identifying the spectral type of every cone in the field of view; computing the per-cone activation the target percept would have produced. (v) Intensities of visible-wavelength 488-nm laser microdoses at each cone required to achieve its target activation level. (C) Infrared imaging and visible-wavelength stimulation are physically accomplished in a raster scan across the retinal region using AOSLO. By modulating the visible-wavelength beam’s intensity, the laser microdoses shown in (v) are delivered. Drawing adapted with permission [Harmening and Sincich (54)]. (D) Examples of target percepts with corresponding cone activations and laser microdoses, ranging from colored squares to complex imagery. Teal-striped regions represent the color “olo” of stimulating only M cones. 
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VES Cinematic Color – Motion-Picture Color ManagementRead more: VES Cinematic Color – Motion-Picture Color ManagementThis paper presents an introduction to the color pipelines behind modern feature-film visual-effects and animation. Authored by Jeremy Selan, and reviewed by the members of the VES Technology Committee including Rob Bredow, Dan Candela, Nick Cannon, Paul Debevec, Ray Feeney, Andy Hendrickson, Gautham Krishnamurti, Sam Richards, Jordan Soles, and Sebastian Sylwan. 
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Photography Basics : Spectral Sensitivity Estimation Without a CameraRead more: Photography Basics : Spectral Sensitivity Estimation Without a Camerahttps://color-lab-eilat.github.io/Spectral-sensitivity-estimation-web/ A number of problems in computer vision and related fields would be mitigated if camera spectral sensitivities were known. As consumer cameras are not designed for high-precision visual tasks, manufacturers do not disclose spectral sensitivities. Their estimation requires a costly optical setup, which triggered researchers to come up with numerous indirect methods that aim to lower cost and complexity by using color targets. However, the use of color targets gives rise to new complications that make the estimation more difficult, and consequently, there currently exists no simple, low-cost, robust go-to method for spectral sensitivity estimation that non-specialized research labs can adopt. Furthermore, even if not limited by hardware or cost, researchers frequently work with imagery from multiple cameras that they do not have in their possession. To provide a practical solution to this problem, we propose a framework for spectral sensitivity estimation that not only does not require any hardware (including a color target), but also does not require physical access to the camera itself. Similar to other work, we formulate an optimization problem that minimizes a two-term objective function: a camera-specific term from a system of equations, and a universal term that bounds the solution space. Different than other work, we utilize publicly available high-quality calibration data to construct both terms. We use the colorimetric mapping matrices provided by the Adobe DNG Converter to formulate the camera-specific system of equations, and constrain the solutions using an autoencoder trained on a database of ground-truth curves. On average, we achieve reconstruction errors as low as those that can arise due to manufacturing imperfections between two copies of the same camera. We provide predicted sensitivities for more than 1,000 cameras that the Adobe DNG Converter currently supports, and discuss which tasks can become trivial when camera responses are available.  
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The Forbidden colors – Red-Green & Blue-Yellow: The Stunning Colors You Can’t SeeRead more: The Forbidden colors – Red-Green & Blue-Yellow: The Stunning Colors You Can’t Seewww.livescience.com/17948-red-green-blue-yellow-stunning-colors.html  While the human eye has red, green, and blue-sensing cones, those cones are cross-wired in the retina to produce a luminance channel plus a red-green and a blue-yellow channel, and it’s data in that color space (known technically as “LAB”) that goes to the brain. That’s why we can’t perceive a reddish-green or a yellowish-blue, whereas such colors can be represented in the RGB color space used by digital cameras. https://en.rockcontent.com/blog/the-use-of-yellow-in-data-design The back of the retina is covered in light-sensitive neurons known as cone cells and rod cells. There are three types of cone cells, each sensitive to different ranges of light. These ranges overlap, but for convenience the cones are referred to as blue (short-wavelength), green (medium-wavelength), and red (long-wavelength). The rod cells are primarily used in low-light situations, so we’ll ignore those for now. When light enters the eye and hits the cone cells, the cones get excited and send signals to the brain through the visual cortex. Different wavelengths of light excite different combinations of cones to varying levels, which generates our perception of color. You can see that the red cones are most sensitive to light, and the blue cones are least sensitive. The sensitivity of green and red cones overlaps for most of the visible spectrum.  Here’s how your brain takes the signals of light intensity from the cones and turns it into color information. To see red or green, your brain finds the difference between the levels of excitement in your red and green cones. This is the red-green channel. To get “brightness,” your brain combines the excitement of your red and green cones. This creates the luminance, or black-white, channel. To see yellow or blue, your brain then finds the difference between this luminance signal and the excitement of your blue cones. This is the yellow-blue channel. From the calculations made in the brain along those three channels, we get four basic colors: blue, green, yellow, and red. Seeing blue is what you experience when low-wavelength light excites the blue cones more than the green and red. Seeing green happens when light excites the green cones more than the red cones. Seeing red happens when only the red cones are excited by high-wavelength light. Here’s where it gets interesting. Seeing yellow is what happens when BOTH the green AND red cones are highly excited near their peak sensitivity. This is the biggest collective excitement that your cones ever have, aside from seeing pure white. Notice that yellow occurs at peak intensity in the graph to the right. Further, the lens and cornea of the eye happen to block shorter wavelengths, reducing sensitivity to blue and violet light. 
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The 7 key elements of brand identity design + 10 corporate identity examplesRead more: The 7 key elements of brand identity design + 10 corporate identity exampleswww.lucidpress.com/blog/the-7-key-elements-of-brand-identity-design 1. Clear brand purpose and positioning 2. Thorough market research 3. Likable brand personality 4. Memorable logo 5. Attractive color palette 6. Professional typography 7. On-brand supporting graphics 
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OLED vs QLED – What TV is better?Read more: OLED vs QLED – What TV is better?Supported by LG, Philips, Panasonic and Sony sell the OLED system TVs. 
 OLED stands for “organic light emitting diode.”
 It is a fundamentally different technology from LCD, the major type of TV today.
 OLED is “emissive,” meaning the pixels emit their own light.Samsung is branding its best TVs with a new acronym: “QLED” 
 QLED (according to Samsung) stands for “quantum dot LED TV.”
 It is a variation of the common LED LCD, adding a quantum dot film to the LCD “sandwich.”
 QLED, like LCD, is, in its current form, “transmissive” and relies on an LED backlight.OLED is the only technology capable of absolute blacks and extremely bright whites on a per-pixel basis. LCD definitely can’t do that, and even the vaunted, beloved, dearly departed plasma couldn’t do absolute blacks. QLED, as an improvement over OLED, significantly improves the picture quality. QLED can produce an even wider range of colors than OLED, which says something about this new tech. QLED is also known to produce up to 40% higher luminance efficiency than OLED technology. Further, many tests conclude that QLED is far more efficient in terms of power consumption than its predecessor, OLED. 
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Polarised vs unpolarized filteringRead more: Polarised vs unpolarized filteringA light wave that is vibrating in more than one plane is referred to as unpolarized light. … Polarized light waves are light waves in which the vibrations occur in a single plane. The process of transforming unpolarized light into polarized light is known as polarization.  en.wikipedia.org/wiki/Polarizing_filter_(photography) The most common use of polarized technology is to reduce lighting complexity on the subject. (more…)
 Details such as glare and hard edges are not removed, but greatly reduced.
LIGHTING
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ICLight – Krea and ComfyUI light editingRead more: ICLight – Krea and ComfyUI light editinghttps://drive.google.com/drive/folders/16Aq1mqZKP-h8vApaN4FX5at3acidqPUv https://github.com/lllyasviel/IC-Light https://generativematte.blogspot.com/2025/03/comfyui-ic-light-relighting-exploration.html  Workflow Local copy  
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Composition and The Expressive Nature Of LightRead 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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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.
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7 Easy Portrait Lighting SetupsRead more: 7 Easy Portrait Lighting SetupsButterfly Loop Rembrandt Split Rim Broad Short 
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Disney’s Moana Island Scene – Free data setRead more: Disney’s Moana Island Scene – Free data sethttps://www.disneyanimation.com/resources/moana-island-scene/ This data set contains everything necessary to render a version of the Motunui island featured in the 2016 film Moana. 
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