Wi-Fi signals let researchers ID people through walls from their gait
Yasamin Mostofi asks us to imagine this scenario: police have video footage of a robbery. They suspect that one of the robbers is hiding in a house nearby.
Can a pair of off-the-shelf Wi-Fi transceivers, located outside the house, look through the walls to see who’s inside?
That’s easy to answer, since we’ve seen it done before.
In 2015, MIT researchers created a device that can discern where you are and who you are, detecting gestures and body movements as subtle as the rise and fall of a person’s chest, from the other side of a house, through a wall, even though subjects were invisible to the naked eye, by using the human body’s reflections of wireless transmissions.
Then, 11 months ago, a team of researchers at University of California Santa Barbara demonstrated using a streamlined set of technologies – just a smartphone and some clever computation – how to see through walls and successfully track people in 11 real-world locations, with high accuracy.
But here’s a new question: Can Wi-Fi signals be used to identify the person in the house? Can off-the-shelf hardware determine if whoever’s in the house is one of the people in the video surveillance footage police are scrutinizing?
Yes. UC Santa Barbara researchers are back again to show that they’ve built on their previous work: It can be done by analyzing people’s walking gaits and comparing them to the gait of whoever’s in the CCTV footage.
Mostofi, a professor of electrical and computer engineering at UC Santa Barbara, is the research lead behind XModal-ID: a proposed approach to using Wi-Fi signals to identify people from their walking gait.