MIT News: A design tool to democratize the art of color-changing mosaics. “Computational tool from MIT CSAIL enables color-changing cellulose-based designs for data visualization, education, fashion, and more.”
University of Waterloo: Computer scientists paint a picture of six decades of movies. “From the sepia tones of a Coen brothers film set in the Depression-era Dust Bowl to a child’s red coat in Schindler’s List, filmmakers have long known the power of colour in movies. Now, computer scientists have analyzed 60 years of films to paint a picture of the past six decades in film.”
News@Northeastern: Machine Vision Breakthrough: This Device Can See ‘Millions Of Colors’. “An interdisciplinary team of researchers at Northeastern have built a device that can recognize ‘millions of colors’ using new artificial intelligence techniques—a massive step, they say, in the field of machine vision, a highly specialized space with broad applications for a range of technologies.”
New York Times: That Painted Greek Maiden at the Met: Just Whose Vision Is She? . “Two German archaeologists use science to recreate the lost colors of antiquity. Historians debate just how authentic their version of the past really is.”
Los Alamos National Laboratory: Math error: A new study overturns 100-year-old understanding of color perception. “A paradigm shift away from the 3D mathematical description developed by Schrödinger and others to describe how we see color could yield more vibrant computer displays, TVs, printed materials, textiles and more.”
Fast Company: This new AI-powered paint tool helps you create custom colors with your voice. “If an architect wanted to create a building that matched the color of a New York City summer sunset, they’d have to pore over potentially hundreds of color cards designed for industry to get anything close, and still it’d be a tall order to find that exact match. But a new AI-powered, voice-controlled tool from Sherwin-Williams aims to change that. The paint brand recently launched Speaking in Color, a tool that allows users to tell it about certain places, objects, or shades in order to arrive at that perfect color.”
Mozilla Blog: Firefox Extension Helps Bring Movie Magic To Theaters Near You. “Color calibration — the process of adjusting colors in order to display images consistently in color and brightness across monitors — is a critical component of visual effects. As visual effects studios and their vendors transitioned to remote work due to the coronavirus pandemic, this process that was easy to manage in-office suddenly became difficult to achieve. Over the past year, Firefox worked with Industrial Light & Magic to build a game-changing solution and developed the Extended Color Management Add-On.”
I gave up on keeping up with the entire Web around about 1996, and I’m *still* delighted when I discover something that’s been quietly trucking along for ages doing good work. Check out Timeline of Historical Film Colors. From the About page: “This database was created in 2012 and has been developed and curated by Barbara Flueckiger, professor at the Department of Film Studies, University of Zurich to provide comprehensive information about historical film color processes invented since the end of the 19th century including specific still photography color technologies that were their conceptual predecessors.”
Smashing Magazine: Color Tools And Resources. “Do you need a little inspiration boost? We’ve collected some useful color tools and resources that we’ve discovered lately — to help you get the most out of your creativity. We’ve also just recently covered CSS auditing tools, CSS generators, accessible front-end components, front-end boilerplates and VS code extensions — you might find them useful, too.”
MakeUseOf: 5 Apps to Find the Best Color Schemes, Matches, and Palettes. “Color is all around us, but not everyone is born with a sense of how to match different hues. But don’t worry, there’s an app for that. In fact, there are several to suggest color schemes, matches, and entire palettes.”
Google Blog: When fashion and choreography meet artificial intelligence. “For our first experiment, Runway Palette, we came together with The Business of Fashion, whose collection includes 140,000 photos of runway looks from almost 4,000 fashion shows. If you could attend one fashion show per day, it would take you more than ten years to see them all. By extracting the main colors of each look, we used machine learning to organize the images by color palette, resulting in an interactive visualization of four years of fashion by almost 1,000 designers.”
Fast Company Design: Google’s Latest Experiment Is Like Reverse Image Search For Color. “Google’s Art & Culture Experiments are always a source of joy–like its recent viral selfie feature, which matched your face to your long-lost twin in fine art. But the app also provides more useful tools, like its latest, Art Palette. It’s a web app that takes any color combination you choose and matches it with artworks drawn from Google’s long list of institutional partners, including thousands of paintings in museums all over the world.”
Phys.org: Colorizing images with deep neural networks . “For decades, image colorization has enjoyed an enduring interest from the public. Though not without its share of detractors, there is something powerful about this simple act of adding color to black and white imagery, whether it be a way of bridging memories between the generations, or expressing artistic creativity. However, the process of manually adding color can be very time consuming and require expertise, with typical professional processes taking hours or days per image to perfect. A team of researchers has proposed a new technique to leverage deep networks and AI, which allows novices, even those with limited artistic ability, to quickly produce reasonable results.”
You can have trouble distinguishing colors on the Web but not be colorblind. A new tool aims to held designers identify which color palettes are most accessible. “Christopher Brooks, [University of Michigan] research assistant professor of information, and colleagues surveyed more than 30,000 people to examine how dim conditions and bright sunlight, in addition to varied abilities, can influence how people differentiate color. The researchers then used the survey results to develop ColorCheck, a web tool that can help digital designers see what colors large swaths of their audiences can’t. The software compares color pairs and tells designers what portion of an image’s hues certain percentages of the population can and can’t tell apart. ColorCheck also pinpoints trouble spots on an image by laying a mask of black pixels over them.”
A researcher is working on a way to have a neural network colorize black and white photos. “In a new paper titled ‘Colorful Image Colorization,’ UC Berkeley computer vision PhD student Richard Zhang and his team share how they’re using a ‘convolutional neural network’ to create automatic colorizations that can often fool humans.” It’s not perfect — read the article to see how perfect it isn’t — but for a beginning technology and for automatic coloring, it’s remarkable.
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