RFPose-OT：基于最优传输理论的RF三维人体姿态估计
RFPose-OT: RF-Based 3D Human Pose Estimation via Optimal Transport Theory
摘要：
本文介绍了一种新的框架，即，RFPose-OT，用于根据射频（RF）信号进行3D人体姿势估计。与现有的直接从信号层上预测人体姿态的方法不同，本文考虑了射频信号与人体姿态之间的结构差异，提出基于最优传输（OT）理论将射频信号变换到特征层上的姿态域，并由变换后的特征生成人体姿态。为了评估RFPose-OT，我们建立了一个无线电系统和一个多视图相机系统来获取RF信号数据和地面真实的人体姿势。在基本室内环境、遮挡室内环境和室外环境中的实验结果都表明，RFPose-OT能够以比现有方法更高的精度预测3D人体姿势。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
