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Seeing Through Walls

By Neil Savage

Communications of the ACM, Vol. 63 No. 6, Pages 15-16

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Machine vision coupled with artificial intelligence (AI) has made great strides toward letting computers understand images. Thanks to deep learning, which processes information in a way analogous to the human brain, machine vision is doing everything from keeping self-driving cars on the right track to improving cancer diagnosis by examining biopsy slides or x-ray images. Now some researchers are going beyond what the human eye or a camera lens can see, using machine learning to watch what people are doing on the other side of a wall.

The technique relies on low-power radio frequency (RF) signals, which reflect off living tissue and metal but pass easily through wooden or plaster interior walls. AI can decipher those signals, not only to detect the presence of people, but also to see how they are moving, and even to predict the activity they are engaged in, from talking on a phone to brushing their teeth. With RF signals, "they can see in the dark. They can see through walls or furniture," says Tianhong Li, a Ph.D. student in the Computer Science and Artificial Intelligence Laboratory at the Massachusetts Institute of Technology (MIT). He and fellow graduate student Lijie Fan helped develop a system to measure movement and, from that, to identify specific actions. "Our goal is to understand what people are doing," Li says.


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