Holographic TV

April 24, 2015
Claro Holographic TV and Media

The Consumer Electronics Show in Las Vegas in January 2010 was abuzz about a slew of prototype 3-D TVs, but if new research from the MIT Media Lab is any indication, holographic TVs could be close behind. At the Society of Photo-Optical Instrumentation Engineers’ (SPIE) Practical Holography conference in San Francisco the weekend of Jan. 23, members of Michael Bove’s Object-Based Media Group presented a new system that can capture visual information using off-the-shelf electronics, send it over the Internet to a holographic display, and update the image at rates approaching those of feature films.

In November, researchers at the University of Arizona made headlines with an experimental holographic-video transmission system that used 16 cameras to capture data and whose display refreshed every two seconds. The new MIT system uses only one data-capture device — the new Kinect camera designed for Microsoft’s Xbox gaming system — and averages about 15 frames per second. Moreover, the MIT researchers didn’t get their hands on a Kinect until the end of December, and only in the week before the conference did they double the system’s frame rate from seven to 15 frames per second. They’re confident that with a little more time, they can boost the rate even higher, to the 24 frames per second of feature films or the 30 frames per second of TV — rates that create the illusion of continuous motion.

The difference between holograms and the type of 3-D images becoming common in movie theaters is frequently overlooked, Bove says. During a screening of, say, the 3-D version of Avatar, viewers on the far-left aisle of the theater see the same image that viewers on the far-right aisle do. That image may have depth, but it’s filmed from a single perspective. As a viewer moves around a hologram, however, his or her perspective on the depicted object changes continuously, just as it would if the object were real.

All the angles

A standard 3-D movie camera captures light bouncing off of an object at two different angles, one for each eye. But in the real world, light bounces off of objects at an infinite number of angles. Holographic video systems use devices that produce so-called diffraction fringes, fine patterns of light and dark that can bend the light passing through them in predictable ways. A dense enough array of fringe patterns, each bending light in a different direction, can simulate the effect of light bouncing off of a three-dimensional object.

The challenge with real-time holographic video is taking video data — in the case of the Kinect, the light intensity of image pixels and, for each of them, a measure of distance from the camera — and, on the fly, converting that data into a set of fringe patterns. Bove and his grad students — James Barabas, David Cranor, Sundeep Jolly and Dan Smalley — have made that challenge even tougher by limiting themselves to off-the-shelf hardware.

“Really, the focus of our work in digital holography — and I think this makes us pretty much unique among the very small community of people in the world even doing holovideo — is that we’re trying to make a consumer product, ” Bove says. “So we’ve been saying, ‘How do you make it as cheap as possible — take advantage of hardware and standards and software and everything else that already exists?’ Because that’s the quickest way to bring it to market.”

Using a single Kinect camera and standard graphics chips, MIT researchers demonstrate the highest frame rate yet for streaming holographic video.
Video: Melanie Gonick; additional stills: James D. Barabas

In the group’s lab setup, the Kinect feeds data to an ordinary laptop, which relays it over the Internet. At the receiving end, a PC with three commercial graphics processing units — GPUs — computes the diffraction patterns.

GPUs differ from ordinary computer chips — CPUs — in that their circuitry has been tailored to a cluster of computationally intensive tasks that arise frequently during the processing of large graphics files. Much of the work that went into the new system involved re-describing the problem of computing diffraction patterns in a way that takes advantage of GPUs’ strengths.

Source: news.mit.edu
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