“We developed a deep neural network that maps the phase and amplitude of WiFi signals to UV coordinates within 24 human regions. The results of the study reveal that our model can estimate the dense pose of multiple subjects, with comparable performance to image-based approaches, by utilizing WiFi signals as the only input.”
Read MoreResearchers have been working on ways to “see” people without using cameras or expensive LiDAR hardware for years. In 2013, a team of researchers at MIT found a way to use cell phone signals to see through walls. In 2018, another MIT team used Wi-Fi to detect people in another room and translate their movements into walking stick figures. Now, researchers at Carnegie Mellon University and the University of Waterloo are advancing our ability to see through walls using Wi-Fi.
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