Superman isn’t the only one with X-ray vision. Now, researchers can detect a person on the other side of a solid wall.

The technology, called RF-Capture, was developed by MIT grad student Fadel Adib and his colleagues at the Institute’s Computer Science and Artificial Intelligence Lab.

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RF-Capture works, not by using X rays, but by with Wi-Fi signals. It sends them through a wall, where they bounce off a person’s body and then when the signal comes back, special software is used to analyze it.

The software is made from a series of algorithms designed to minimize the noise that’s produced by the signal reflections and helps the researchers create more distinct images of the person’s body.

The imaging works so well that the scientists can detect gestures and body motions as subtle as the rise and fall of a person’s chest or trace a person’s hand writing in the air. It can identify who the person is, where he is located and which hand he’s moving or what his posture is like.

See the video below for more details.

RF-Capture can distinguish among up to 15 individuals from behind a wall with a surprising 90 percent accuracy rate.

The device was first conceptualized back in 2012 when Adib began contemplating how Wi-Fi could be used to see through walls. Although the device has been under development for some time, it hasn’t been able to distinguish individuals until just recently.

The team plans to launch a startup in 2016 to commercialize on the technology, which would open up a huge realm of possibilities, from bolstering search and rescue operations such as firefighters looking for survivors to monitoring people at home who are at risk for falling and needing help.

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On a lighter note, the technology can also be used to inject special effects into Hollywood films, like enabling motion capture without body sensors and tracking actors’ movements from behind objects or walls.

“The possibilities are vast,” says Adib, whose other co-authors include MIT professor Frédo Durand, PhD student Chen-Yu Hsu, and undergraduate intern Hongzi Mao, according to MIT. “We’re just at the beginning of thinking about the different ways to use these technologies.”

The team’s paper was accepted to the SIGGRAPH Asia conference taking place this month.