![]() But could it still be considered “painting”? Many filmmakers and cinematographers, the hands-on visionaries of light, have embraced the ease, crispness, and immediacy of digital media as a technological and artistic great leap forward, while others believe that a craft that had reached a highly attuned level of precision over the last few decades is being jettisoned in the name of needless novelty. Great artists would still produce great work, of course. It’s almost as if the oil-based paints that emerged in the Middle Ages, and have remained the dominant, high-prestige medium in the visual arts ever since, had suddenly been replaced with some entirely different medium. It’s not easy to find a historical parallel for this. ![]() If film as a medium is not quite dead, it’s definitely on the endangered list. What you see on the screen is no longer a light bulb shining through a strip of 35mm film, but the output of a concatenation of files called a Digital Cinema Package, or DCP, delivered to the theater on a hard drive or securely downloaded from the Internet. Indeed, most commercial mainstream cinema is now a digital process from beginning to end, from the set to the editing suite to the projection booth at your neighborhood multiplex. Most Hollywood movies, and for that matter, most movies made anywhere in the world, are no longer shot on photographic film, but made with digital cameras and recorded as bytes and pixels, ones and zeroes, through a process that appears transparent but some filmmakers find distressingly mysterious. But over the course of the last decade, filmmaking has undergone a technical revolution. ![]() Sometimes it’s the apex of simplicity, a technique so transparent it appears almost artless, as in the black-and-white compositions of Robert Bresson or the free-form streetscapes of Richard Linklater’s Slacker.įor 100 years and more, while the technique and style of cinema evolved and varied immensely, its underlying scientific and technological basis remained virtually unchanged: the seductive grain of the film image, the whir of the projector, the organic flow of light into the camera and onto the screen. Sometimes the captured light of cinema amounts to an aesthetic revolution, as with the deep-focus cinematography of Gregg Toland in Orson Welles’ landmark Citizen Kane, the spectacular wide-screen landscapes shot by Freddie Young in Lawrence of Arabia, or the super-slo-mo “bullet time” cinematography of The Matrix. Part two runs tomorrow part three runs on Friday.Ĭinema is a blend of art and technology, working together to capture light, one frame at a time, to create the illusion of motion. This is part one of a three-part series about the movie industry’s switch to digital cameras and what is lost, and gained, in the process. This network is demonstrated to accurately synthesize defocus blur, focal stacks, multilayer decompositions, and multiview imagery using only commonly available RGB-D images, enabling real-time, near-correct depictions of retinal blur with a broad set of accommodation-supporting HMDs.A landmark use of deep focus in film: The young Charles Foster Kane-in the background, but still in focus-is sent away by his poor parents in Colorado to live with a wealthy banker in New York. In this paper, we introduce DeepFocus, a generic, end-to-end convolutional neural network designed to efficiently solve the full range of computational tasks for accommodation-supporting HMDs. To date, no unified framework has been proposed to support driving these emerging HMDs using commodity content. These designs all extend depth of focus, but rely on computationally expensive rendering and optimization algorithms to reproduce accurate defocus blur (often limiting content complexity and interactive applications). ![]() A multitude of accommodation-supporting HMDs have been proposed, with three architectures receiving particular attention: varifocal, multifocal, and light field displays. Second, HMDs should accurately reproduce retinal defocus blur to correctly drive accommodation. First, the hardware must support viewing sharp imagery over the full accommodation range of the user. ![]() Kaplanyan, Alexander Fix, Matthew Chapman, Douglas LanmanĪddressing vergence-accommodation conflict in head-mounted displays (HMDs) requires resolving two interrelated problems. Title: DeepFocus: Learned Image Synthesis for Computational Displays Note: We don't have the ability to review paper ![]()
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