MagShield: Towards Better Robustness in Sparse Inertial Motion Capture Under Magnetic Disturbances
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Abstract (arXiv)
This paper proposes a novel method called MagShield, designed to address the issue of magnetic interference in sparse inertial motion capture (MoCap) systems. Existing Inertial Measurement Unit (IMU) systems are prone to orientation estimation errors in magnetically disturbed environments, limiting their practical application in real-world scenarios. To address this problem, MagShield employs a "detect-then-correct" strategy, first detecting magnetic disturbances through multi-IMU joint analysis, and then correcting orientation errors using human motion priors. MagShield can be integrated with most existing sparse inertial MoCap systems, improving their performance in magnetically disturbed environments. Experimental results demonstrate that MagShield significantly enhances the accuracy of motion capture under magnetic interference and exhibits good compatibility across different sparse inertial MoCap systems.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 11 of its 32 references that are in the map. First posted on arXiv 28 Jun 2025.
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11 of 32 references.
References · 11
- 2019AMASS: Archive of Motion Capture as Surface Shapescited by 1,236
- 2022Physical Inertial Poser (PIP): Physics-aware Real-time Human Motion Tracking from Sparse Inertial Sensorscited by 146
- 2017Sparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUscited by 109
- 2022Transformer Inertial Poser: Real-time Human Motion Reconstruction from Sparse IMUs with Simultaneous Terrain Generationcited by 76
- 2023IMUPoser: Full-Body Pose Estimation using IMUs in Phones, Watches, and Earbudscited by 54
- 2023DiffusionPoser: Real-time Human Motion Reconstruction From Arbitrary Sparse Sensors Using Autoregressive Diffusioncited by 31
- 2017Quaternion kinematics for the error-state Kalman filtercited by 30
- 2023Dynamic Inertial Poser (DynaIP): Part-Based Motion Dynamics Learning for Enhanced Human Pose Estimation with Sparse Inertial Sensorscited by 30
- 2024Physical Non-inertial Poser (PNP): Modeling Non-inertial Effects in Sparse-inertial Human Motion Capturecited by 24
- 2025MobilePoser: Real-Time Full-Body Pose Estimation and 3D Human Translation from IMUs in Mobile Consumer Devicescited by 23
- 2022VQF: Highly Accurate IMU Orientation Estimation with Bias Estimation and Magnetic Disturbance Rejectioncited by 7
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Citing papers per year: 2026: 2.
2 papers.