COMPOSITION
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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.
What type of lighting?-> High key lighting.
Features bright, even illumination and few conspicuous shadows. This lighting key is often used in musicals and comedies.Low key lighting
Features diffused shadows and atmospheric pools of light. This lighting key is often used in mysteries and thrillers.High contrast lighting
Features harsh shafts of lights and dramatic streaks of blackness. This type of lighting is often used in tragedies and melodramas.What type of shot?
Extreme long shot
Taken from a great distance, showing much of the locale. Ifpeople are included in these shots, they usually appear as mere specks-> Long shot
Corresponds to the space between the audience and the stage in a live theater. The long shots show the characters and some of the locale.Full shot
Range with just enough space to contain the human body in full. The full shot shows the character and a minimal amount of the locale.Medium shot
Shows the human figure from the knees or waist up.Close-Up
Concentrates on a relatively small object and show very little if any locale.Extreme close-up
Focuses on an unnaturally small portion of an object, giving that part great detail and symbolic significance.What angle?
Bird’s-eye view.
The shot is photographed directly from above. This type of shot can be disorienting, and the people photographed seem insignificant.High angle.
This angle reduces the size of the objects photographed. A person photographed from this angle seems harmless and insignificant, but to a lesser extent than with the bird’s-eye view.-> Eye-level shot.
The clearest view of an object, but seldom intrinsically dramatic, because it tends to be the norm.Low angle.
This angle increases high and a sense of verticality, heightening the importance of the object photographed. A person shot from this angle is given a sense of power and respect.Oblique angle.
For this angle, the camera is tilted laterally, giving the image a slanted appearance. Oblique angles suggest tension, transition, a impending movement. They are also called canted or dutch angles.What is the dominant color?
The use of color in this shot is symbolic. The scene is set in warehouse. Both the set and characters are blues, blacks and whites.
This was intentional allowing for the scenes and shots with blood to have a great level of contrast.
What is the Lens/Filter/Stock?
Telephoto lens.
A lens that draws objects closer but also diminishes the illusion of depth.Wide-angle lens.
A lens that takes in a broad area and increases the illusion of depth but sometimes distorts the edges of the image.Fast film stock.
Highly sensitive to light, it can register an image with little illumination. However, the final product tends to be grainy.Slow film stock.
Relatively insensitive to light, it requires a great deal of illumination. The final product tends to look polished.The lens is not wide-angle because there isn’t a great sense of depth, nor are several planes in focus. The lens is probably long but not necessarily a telephoto lens because the depth isn’t inordinately compressed.
The stock is fast because of the grainy quality of the image.
Subsidiary Contrast; where does the eye go next?
The two guns.
How much visual information is packed into the image? Is the texture stark, moderate, or highly detailed?
Minimalist clutter in the warehouse allows a focus on a character driven thriller.
What is the Composition?
Horizontal.
Compositions based on horizontal lines seem visually at rest and suggest placidity or peacefulness.Vertical.
Compositions based on vertical lines seem visually at rest and suggest strength.-> Diagonal.
Compositions based on diagonal, or oblique, lines seem dynamic and suggest tension or anxiety.-> Binary. Binary structures emphasize parallelism.
Triangle.
Triadic compositions stress the dynamic interplay among three mainCircle.
Circular compositions suggest security and enclosure.Is the form open or closed? Does the image suggest a window that arbitrarily isolates a fragment of the scene? Or a proscenium arch, in which the visual elements are carefully arranged and held in balance?
The most nebulous of all the categories of mise en scene, the type of form is determined by how consciously structured the mise en scene is. Open forms stress apparently simple techniques, because with these unself-conscious methods the filmmaker is able to emphasize the immediate, the familiar, the intimate aspects of reality. In open-form images, the frame tends to be deemphasized. In closed form images, all the necessary information is carefully structured within the confines of the frame. Space seems enclosed and self-contained rather than continuous.
Could argue this is a proscenium arch because this is such a classic shot with parallels and juxtapositions.
Is the framing tight or loose? Do the character have no room to move around, or can they move freely without impediments?
Shots where the characters are placed at the edges of the frame and have little room to move around within the frame are considered tight.
Longer shots, in which characters have room to move around within the frame, are considered loose and tend to suggest freedom.
Center-framed giving us the entire scene showing isolation, place and struggle.
Depth of Field. On how many planes is the image composed (how many are in focus)? Does the background or foreground comment in any way on the mid-ground?
Standard DOF, one background and clearly defined foreground.
Which way do the characters look vis-a-vis the camera?
An actor can be photographed in any of five basic positions, each conveying different psychological overtones.
Full-front (facing the camera):
the position with the most intimacy. The character is looking in our direction, inviting our complicity.Quarter Turn:
the favored position of most filmmakers. This position offers a high degree of intimacy but with less emotional involvement than the full-front.-> Profile (looking of the frame left or right):
More remote than the quarter turn, the character in profile seems unaware of being observed, lost in his or her own thoughts.Three-quarter Turn:
More anonymous than the profile, this position is useful for conveying a character’s unfriendly or antisocial feelings, for in effect, the character is partially turning his or her back on us, rejecting our interest.Back to Camera:
The most anonymous of all positions, this position is often used to suggest a character’s alienation from the world. When a character has his or her back to the camera, we can only guess what’s taking place internally, conveying a sense of concealment, or mystery.How much space is there between the characters?
Extremely close, for a gunfight.
The way people use space can be divided into four proxemic patterns.
Intimate distances.
The intimate distance ranges from skin contact to about eighteen inches away. This is the distance of physical involvement–of love, comfort, and tenderness between individuals.-> Personal distances.
The personal distance ranges roughly from eighteen inches away to about four feet away. These distances tend to be reserved for friends and acquaintances. Personal distances preserve the privacy between individuals, yet these rages don’t necessarily suggest exclusion, as intimate distances often do.Social distances.
The social distance rages from four feet to about twelve feet. These distances are usually reserved for impersonal business and casual social gatherings. It’s a friendly range in most cases, yet somewhat more formal than the personal distance.Public distances.
The public distance extends from twelve feet to twenty-five feet or more. This range tends to be formal and rather detached.
DESIGN
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The illusion of sex 2009
Richard Russell Harvard University, USA
In the Illusion of Sex, two faces are perceived as male and female.
However, both faces are actually versions of the same androgynous face.
One face was created by increasing the contrast of the androgynous face, while the other face was created by decreasing the contrast. The face with more contrast is perceived as female, while the face with less contrast is perceived as male. The Illusion of Sex demonstrates that contrast is an important cue for perceiving the sex of a face, with greater contrast appearing feminine, and lesser contrast appearing masculine.
Russell, R. (2009) A sex difference in facial pigmentation and its exaggeration by cosmetics. Perception, (38)1211-1219.
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Public Work – A search engine for free public domain content
Read more: Public Work – A search engine for free public domain contentExplore 100,000+ copyright-free images from The MET, New York Public Library, and other sources.
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Arminas Valunas – “Coca-Cola: Wherever you are.”
Arminas created this using Juggernaut Xl model and QR Code Monster SDXL ControlNet.
His pipeline:
Static Images – Forge UI.
Upscaled with Leonardo AI universal upscaler.
Animated with Runway ML and Minimax.
Video upscale – Topaz Video AI.
Composited in Adobe Premiere.
Juggernaut Xl download here:
https://civitai.com/models/133005/juggernaut-xl
QR Code Monster SDXL:
https://civitai.com/models/197247?modelVersionId=221829
COLOR
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Björn Ottosson – OKHSV and OKHSL – Two new color spaces for color picking
Read 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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Thomas Mansencal – Colour Science for Python
Read more: Thomas Mansencal – Colour Science for Pythonhttps://thomasmansencal.substack.com/p/colour-science-for-python
https://www.colour-science.org/
Colour is an open-source Python package providing a comprehensive number of algorithms and datasets for colour science. It is freely available under the BSD-3-Clause terms.
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What is OLED and what can it do for your TV
Read more: What is OLED and what can it do for your TVhttps://www.cnet.com/news/what-is-oled-and-what-can-it-do-for-your-tv/
OLED stands for Organic Light Emitting Diode. Each pixel in an OLED display is made of a material that glows when you jab it with electricity. Kind of like the heating elements in a toaster, but with less heat and better resolution. This effect is called electroluminescence, which is one of those delightful words that is big, but actually makes sense: “electro” for electricity, “lumin” for light and “escence” for, well, basically “essence.”
OLED TV marketing often claims “infinite” contrast ratios, and while that might sound like typical hyperbole, it’s one of the extremely rare instances where such claims are actually true. Since OLED can produce a perfect black, emitting no light whatsoever, its contrast ratio (expressed as the brightest white divided by the darkest black) is technically infinite.
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.
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VES Cinematic Color – Motion-Picture Color Management
This 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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colorhunt.co
Color Hunt is a free and open platform for color inspiration with thousands of trendy hand-picked color palettes.
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Akiyoshi Kitaoka – Surround biased illumination perception
Read more: Akiyoshi Kitaoka – Surround biased illumination perceptionhttps://x.com/AkiyoshiKitaoka/status/1798705648001327209
The left face appears whitish and the right one blackish, but they are made up of the same luminance.
https://community.wolfram.com/groups/-/m/t/3191015
Illusory staircase Gelb effect
https://www.psy.ritsumei.ac.jp/akitaoka/illgelbe.html
LIGHTING
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Cinematographers Blueprint 300dpi poster
Read more: Cinematographers Blueprint 300dpi posterThe 300dpi digital poster is now available to all PixelSham.com subscribers.
If you have already subscribed and wish a copy, please send me a note through the contact page.
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Is a MacBeth Colour Rendition Chart the Safest Way to Calibrate a Camera?
Read more: Is a MacBeth Colour Rendition Chart the Safest Way to Calibrate a Camera?www.colour-science.org/posts/the-colorchecker-considered-mostly-harmless/
“Unless you have all the relevant spectral measurements, a colour rendition chart should not be used to perform colour-correction of camera imagery but only for white balancing and relative exposure adjustments.”
“Using a colour rendition chart for colour-correction might dramatically increase error if the scene light source spectrum is different from the illuminant used to compute the colour rendition chart’s reference values.”
“other factors make using a colour rendition chart unsuitable for camera calibration:
– Uncontrolled geometry of the colour rendition chart with the incident illumination and the camera.
– Unknown sample reflectances and ageing as the colour of the samples vary with time.
– Low samples count.
– Camera noise and flare.
– Etc…“Those issues are well understood in the VFX industry, and when receiving plates, we almost exclusively use colour rendition charts to white balance and perform relative exposure adjustments, i.e. plate neutralisation.”
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9 Best Hacks to Make a Cinematic Video with Any Camera
Read more: 9 Best Hacks to Make a Cinematic Video with Any Camerahttps://www.flexclip.com/learn/cinematic-video.html
- Frame Your Shots to Create Depth
- Create Shallow Depth of Field
- Avoid Shaky Footage and Use Flexible Camera Movements
- Properly Use Slow Motion
- Use Cinematic Lighting Techniques
- Apply Color Grading
- Use Cinematic Music and SFX
- Add Cinematic Fonts and Text Effects
- Create the Cinematic Bar at the Top and the Bottom
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Outpost VFX lighting tips
Read more: Outpost VFX lighting tipswww.outpost-vfx.com/en/news/18-pro-tips-and-tricks-for-lighting
Get as much information regarding your plate lighting as possible
- Always use a reference
- Replicate what is happening in real life
- Invest into a solid HDRI
- Start Simple
- Observe real world lighting, photography and cinematography
- Don’t neglect the theory
- Learn the difference between realism and photo-realism.
- Keep your scenes organised
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DiffusionLight: HDRI Light Probes for Free by Painting a Chrome Ball
Read more: DiffusionLight: HDRI Light Probes for Free by Painting a Chrome Ballhttps://diffusionlight.github.io/
https://github.com/DiffusionLight/DiffusionLight
https://github.com/DiffusionLight/DiffusionLight?tab=MIT-1-ov-file#readme
https://colab.research.google.com/drive/15pC4qb9mEtRYsW3utXkk-jnaeVxUy-0S
“a simple yet effective technique to estimate lighting in a single input image. Current techniques rely heavily on HDR panorama datasets to train neural networks to regress an input with limited field-of-view to a full environment map. However, these approaches often struggle with real-world, uncontrolled settings due to the limited diversity and size of their datasets. To address this problem, we leverage diffusion models trained on billions of standard images to render a chrome ball into the input image. Despite its simplicity, this task remains challenging: the diffusion models often insert incorrect or inconsistent objects and cannot readily generate images in HDR format. Our research uncovers a surprising relationship between the appearance of chrome balls and the initial diffusion noise map, which we utilize to consistently generate high-quality chrome balls. We further fine-tune an LDR difusion model (Stable Diffusion XL) with LoRA, enabling it to perform exposure bracketing for HDR light estimation. Our method produces convincing light estimates across diverse settings and demonstrates superior generalization to in-the-wild scenarios.”
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