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Soon you too can have 'X-ray vision' for just $300

Soon you too can have 'X-ray vision' for just $300

A new MIT spin-off is scheduled to begin selling the technology in early 2017

It may not be ready for gift-giving this year, but come 2017 this could be the hottest item on wish lists around the world: a $300 device that enables "X-ray vision."

The technology has been under development for more than two years, and now a group of researchers from MIT's Computer Science and Artificial Intelligence Lab (CSAIL) is spinning off a company to market it.

Dubbed RF Capture, the technology senses wireless reflections off the human body and can thereby "see" the silhouette of a human standing behind a wall. From across a building, it can determine where you are, who you are, and even which hand you're moving.

Through a spin-off called Emerald, the plan is reportedly for it to hit the market in early 2017 at a price between $250 and $300.

To work its magic, the device transmits wireless signals that traverse the wall and reflect off a person’s body and then back to the device.

The emitted radiation is approximately 1/10,000 the amount given off by a standard cellphone, MIT says.

From those reflections, the device can see the person’s silhouette. To distinguish among humans, all of which reflect a similar signal, the team developed a series of algorithms. Essentially, the device monitors how human reflections vary as someone moves and then connects each person’s reflections over time into a single, consistent silhouette image.

Privacy questions aside, the technology promises rich applications in movies and gaming as well as smart homes, emergency response and care of the elderly.

In movie production, for example, it could enable motion capture without body sensors and track actors’ movements even if they are behind furniture or walls.

In gaming, players could interact from different rooms or even trigger actions based on which hand they move.

Emerald, meanwhile, will focus on detecting, predicting and preventing falls among the elderly without requiring that they wear a sensor.


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