  This paper introduces a novel framework, i.e., RFPose-OT, to enable the 3D
human pose estimation from Radio Frequency (RF) signals. Different from
existing methods that predict human poses from RF signals on the signal level
directly, we consider the structure difference between the RF signals and the
human poses, propose to transform the RF signals to the pose domain on the
feature level based on Optimal Transport (OT) theory, and generate human poses
from the transformed features. To evaluate RFPose-OT, we build a radio system
and a multi-view camera system to acquire the RF signal data and the
ground-truth human poses. The experimental results in basic indoor environment,
occlusion indoor environment, and outdoor environment, all demonstrate that
RFPose-OT can predict 3D human poses with higher precision than the
state-of-the-art methods.
