  In this paper, we present, Wi-Mesh, a WiFi vision-based 3D human mesh
construction system. Our system leverages the advances of WiFi to visualize the
shape and deformations of the human body for 3D mesh construction. In
particular, it leverages multiple transmitting and receiving antennas on WiFi
devices to estimate the two-dimensional angle of arrival (2D AoA) of the WiFi
signal reflections to enable WiFi devices to see the physical environment as we
humans do. It then extracts only the images of the human body from the physical
environment and leverages deep learning models to digitize the extracted human
body into a 3D mesh representation. Experimental evaluation under various
indoor environments shows that Wi-Mesh achieves an average vertices location
error of 2.81cm and joint position error of 2.4cm, which is comparable to the
systems that utilize specialized and dedicated hardware. The proposed system
has the advantage of re-using the WiFi devices that already exist in the
environment for potential mass adoption. It can also work in non-line of sight
(NLoS), poor lighting conditions, and baggy clothes, where the camera-based
systems do not work well.
