RFPose-OT：基于最优传输理论的无线三维人体姿态估计

俞聪; 张东恒; 武治; 卢智; 解春阳; 胡洋; 陈彦

doi:10.1631/FITEE.2200550

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RFPose-OT：基于最优传输理论的无线三维人体姿态估计

常规文章 | Updated：2023-10-25

- RFPose-OT：基于最优传输理论的无线三维人体姿态估计
  Enhanced Publication
- RFPose-OT: RF-based 3D human pose estimation via optimal transport theory
- 信息与电子工程前沿（英文） 2023年24卷第10期页码：1445-1457
- Affiliations：
  
  1.School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
  2.School of Cyber Science and Technology, University of Science and Technology of China, Hefei 230026, China
  3.School of Information Science and Technology, University of Science and Technology of China, Hefei 230026, China
- Author bio：
  
  †E-mail: congyu@std.uestc.edu.cn
  ‡Corresponding author
- Funds：
  
  National Natural Science Foundation of China(62201542;62172381);National Key R&D Programmes of China(2022YFC2503405;2022YFC0869800);Fellowship of China Postdoctoral Science Foundation(2022M723069);Fundamental Research Funds for the Central Universities, China
- DOI：10.1631/FITEE.2200550
  中图分类号： TP391.4
- 纸质出版日期：2023-10-0 ，
  
  收稿日期：2022-11-07，
  
  录用日期：2023-06-15
- Accepted：
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俞聪, 张东恒, 武治, 等. RFPose-OT：基于最优传输理论的无线三维人体姿态估计[J]. 信息与电子工程前沿（英文）, 2023,24(10):1445-1457.

CONG YU, DONGHENG ZHANG, ZHI WU, et al. RFPose-OT: RF-based 3D human pose estimation via optimal transport theory. [J]. Frontiers of information technology & electronic engineering, 2023, 24(10): 1445-1457.
俞聪, 张东恒, 武治, 等. RFPose-OT：基于最优传输理论的无线三维人体姿态估计[J]. 信息与电子工程前沿（英文）, 2023,24(10):1445-1457. DOI： 10.1631/FITEE.2200550.

CONG YU, DONGHENG ZHANG, ZHI WU, et al. RFPose-OT: RF-based 3D human pose estimation via optimal transport theory. [J]. Frontiers of information technology & electronic engineering, 2023, 24(10): 1445-1457. DOI： 10.1631/FITEE.2200550.

摘要

本文提出一个新颖的RFPose-OT模型框架以实现从无线射频信号中估计三维人体姿态。与现有直接从射频信号中预测人体姿态方法不同，本文考虑射频信号与人体姿态之间的结构特征差异，提出基于最优传输理论在特征空间上将射频信号变换到人体姿态域，再根据变换后的特征预测人体姿态。为评估RFPose-OT模型，本文构建了一个无线电系统和一个多视角相机系统获取无线信号数据以及真实的人体姿态标签。在室内基本环境、室内遮挡环境以及室外环境中的实验结果表明，RFPose-OT模型能精确地估计三维人体姿态，优于现有方法。

Abstract

This paper introduces a novel framework

i.e.

RFPose-OT

to enable three-dimensional (3D) human pose estimation from radio frequency (RF) signals. Different from existing methods that predict human poses from RF signals at the signal level directly

we consider the structure difference between the RF signals and the human poses

propose a transformation of the RF signals to the pose domain at the feature level based on the 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 a basic indoor environment

an occlusion indoor environment

and an outdoor environment demonstrate that RFPose-OT can predict 3D human poses with higher precision than state-of-the-art methods.

关键词

无线射频感知人体姿态估计最优传输深度学习

Keywords

Radio frequency sensingHuman pose estimationOptimal transportDeep learning

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