Embodied mmWave Spotlight: How Stripped-Down mmWave Radars Finally Made Egocentric 3D Human Mesh Reconstruction Practical

Imagine you're at home playing motion-sensing games or perfecting your fitness movements. You want real-time 3D feedback on your posture-whether to correct your form, track progress, or create a lifelike avatar for the metaverse. Yet today's solutions leave you with an unsatisfying choice: point a camera (e.g., RGB, depth, or thermal) at yourself and sacrifice privacy while struggling with varying light conditions and occlusions, or rely on bulky, expensive motion-capture (MoCap) systems that no ordinary person would install at home. Researchers have explored camera-free alternatives based on RF sensing technologies [1-5]—for example, an mmWave radar positioned in front of the user. However, this frontal-view approach suffers from limited sensing range, self-occlusion, and severe multipath interference from walls and furniture-performance collapses the moment the user turns or moves a few steps away.

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Publication Details

Journal
GetMobile Mobile Computing and Communications
Published
2026-07-30
DOI
https://doi.org/10.1145/3833428.3833435
Primary Topic
Indoor and Outdoor Localization Technologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Embodied mmWave Spotlight: How Stripped-Down mmWave Radars Finally Made Egocentric 3D Human Mesh Reconstruction Practical

Weitao Xu, Di Duan, Guoliang Xing, Shengzhe Lyu
GetMobile Mobile Computing and Communications
Indoor and Outdoor Localization Technologies
article

Embodied mmWave Spotlight: How Stripped-Down mmWave Radars Finally Made Egocentric 3D Human Mesh Reconstruction Practical

Weitao Xu, Di Duan, Guoliang Xing, Shengzhe Lyu
article en

Abstract

Imagine you're at home playing motion-sensing games or perfecting your fitness movements. You want real-time 3D feedback on your posture-whether to correct your form, track progress, or create a lifelike avatar for the metaverse. Yet today's solutions leave you with an unsatisfying choice: point a camera (e.g., RGB, depth, or thermal) at yourself and sacrifice privacy while struggling with varying light conditions and occlusions, or rely on bulky, expensive motion-capture (MoCap) systems that no ordinary person would install at home. Researchers have explored camera-free alternatives based on RF sensing technologies [1-5]—for example, an mmWave radar positioned in front of the user. However, this frontal-view approach suffers from limited sensing range, self-occlusion, and severe multipath interference from walls and furniture-performance collapses the moment the user turns or moves a few steps away.

GetMobile Mobile Computing and CommunicationsVol. 30(2)
City University of Hong Kong (HK), Chinese University of Hong Kong (HK)
Openalex Percentile: Top 16%
Indoor and Outdoor Localization Technologies
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