Accurate Human Pose Estimation using RF Signals

Xie, Chunyang; Zhang, Dongheng; Wu, Zhi; Yu, Cong; Hu, Yang; Sun, Quansen; Chen, Yan

doi:10.1109/mmsp55362.2022.9948797

Cited by 4 publications

(1 citation statement)

References 13 publications

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“…Besides, RPM [116] designs a multi-dimensional feature fusion backbone network for human pose estimation. It consists of two blocks: one is a channel fusion block that can effectively fuse horizontal and vertical RF features based on the channels' correlation.…”

Section: Human Imagingmentioning

confidence: 99%

A Survey of mmWave-Based Human Sensing: Technology, Platforms and Applications

Zhang,

Xi,

et al. 2023

IEEE Commun. Surv. Tutorials

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With the rapid development of the Internet of Things (IoT) and the rise of 5G communication networks and automatic driving, millimeter wave (mmWave) sensing is emerging and starts impacting our life and workspace. mmWave sensing can sense humans and objects in a contactless way, providing fine-grained sensing ability. In the past few years, many mmWave sensing techniques have been proposed and applied in various human sensing applications (e.g., human localization, gesture recognition, and vital monitoring). We discover the need of a comprehensive survey to summarize the technology, platforms and applications of mmWave-based human sensing. In this survey, we first present the mmWave hardware platforms and some key techniques of mmWave sensing. We then provide a comprehensive review of existing mmWave-based human sensing works. Specifically, we divide existing works into four categories according to the sensing granularity: human tracking and localization, motion recognition, biometric measurement and human imaging. Finally, we discuss the potential research challenges and present future directions in this area.

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Section: Human Imagingmentioning

confidence: 99%