# MobilePoser: Real-Time Full-Body Pose Estimation and 3D Human Translation from IMUs in Mobile Consumer Devices

arXiv: https://arxiv.org/abs/2504.12492 · HTML: https://mlsanity.com/paper/2504.12492/

## Key facts

- Cited by 23 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 47 references that are in the map.
- First posted on arXiv 16 Apr 2025.

## Builds on (most cited first, 14 of 14)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [AMASS: Archive of Motion Capture as Surface Shapes](https://mlsanity.com/paper/1904.03278/) (2019)
- [Humans in 4D: Reconstructing and Tracking Humans with Transformers](https://mlsanity.com/paper/2305.20091/) (2023)
- [Physical Inertial Poser (PIP): Physics-aware Real-time Human Motion Tracking from Sparse Inertial Sensors](https://mlsanity.com/paper/2203.08528/) (2022)
- [AvatarPoser: Articulated Full-Body Pose Tracking from Sparse Motion Sensing](https://mlsanity.com/paper/2207.13784/) (2022)
- [Sparse Inertial Poser: Automatic 3D Human Pose Estimation from Sparse IMUs](https://mlsanity.com/paper/1703.08014/) (2017)
- [Transformer Inertial Poser: Real-time Human Motion Reconstruction from Sparse IMUs with Simultaneous Terrain Generation](https://mlsanity.com/paper/2203.15720/) (2022)
- [IMUPoser: Full-Body Pose Estimation using IMUs in Phones, Watches, and Earbuds](https://mlsanity.com/paper/2304.12518/) (2023)
- [EgoLocate: Real-time Motion Capture, Localization, and Mapping with Sparse Body-mounted Sensors](https://mlsanity.com/paper/2305.01599/) (2023)
- [Deep Inertial Poser: Learning to Reconstruct Human Pose from Sparse Inertial Measurements in Real Time](https://mlsanity.com/paper/1810.04703/) (2018)
- [RIDI: Robust IMU Double Integration](https://mlsanity.com/paper/1712.09004/) (2017)
- [Mocap Everyone Everywhere: Lightweight Motion Capture With Smartwatches and a Head-Mounted Camera](https://mlsanity.com/paper/2401.00847/) (2024)
- [SparsePoser: Real-time Full-body Motion Reconstruction from Sparse Data](https://mlsanity.com/paper/2311.02191/) (2023)
- [Ultra Inertial Poser: Scalable Motion Capture and Tracking from Sparse Inertial Sensors and Ultra-Wideband Ranging](https://mlsanity.com/paper/2404.19541/) (2024)

## Built on by (most cited first, 23 of 23)

- [Transformer IMU Calibrator: Dynamic On-body IMU Calibration for Inertial Motion Capture](https://mlsanity.com/paper/2506.10580/) (2025)
- [Towards Generalizable Human Activity Recognition: A Survey](https://mlsanity.com/paper/2508.12213/) (2025)
- [ECHO: Ego-Centric modeling of Human-Object interactions](https://mlsanity.com/paper/2508.21556/) (2025)
- [IMUCoCo: Enabling Flexible On-Body IMU Placement for Human Pose Estimation and Activity Recognition](https://mlsanity.com/paper/2508.01894/) (2025)
- [BaroPoser: Real-time Human Motion Tracking from IMUs and Barometers in Everyday Devices](https://mlsanity.com/paper/2508.03313/) (2025)
- [WatchHAR: Real-time On-device Human Activity Recognition System for Smartwatches](https://mlsanity.com/paper/2509.04736/) (2025)
- [MagShield: Towards Better Robustness in Sparse Inertial Motion Capture Under Magnetic Disturbances](https://mlsanity.com/paper/2506.22907/) (2025)
- [Ground Reaction Inertial Poser: Physics-based Human Motion Capture from Sparse IMUs and Insole Pressure Sensors](https://mlsanity.com/paper/2603.16233/) (2026)
- [Seeing Without Eyes: 4D Human-Scene Understanding from Wearable IMUs](https://mlsanity.com/paper/2604.21926/) (2026)
- [Towards Real-World Wearable Motion Reconstruction](https://mlsanity.com/paper/2607.09780/) (2026)
- [Generating Fit Check Videos with a Handheld Camera](https://mlsanity.com/paper/2505.23886/) (2025)
- [From Neck to Head: Bio-Impedance Sensing for Head Pose Estimation](https://mlsanity.com/paper/2507.12884/) (2025)
- [ChairPose: Pressure-based Chair Morphology Grounded Sitting Pose Estimation through Simulation-Assisted Training](https://mlsanity.com/paper/2508.01850/) (2025)
- [Human Motion Estimation with Everyday Wearables](https://mlsanity.com/paper/2512.21209/) (2025)
- [AIGaitor: Privacy-preserving and cloud-free motion analysis for everyone, using edge computing](https://mlsanity.com/paper/2605.21421/) (2026)
- [MARIO: Motion-Augmented Real-Time Multi-Sensor Inertial Odometry](https://mlsanity.com/paper/2606.02996/) (2026)
- [IMU-HOI: A Symbiotic Framework for Coherent Human-Object Interaction and Motion Capture via Contact-Conscious Inertial Fusion](https://mlsanity.com/paper/2606.28604/) (2026)
- [ArmPoser: Real-Time, Calibration-Free Arm Pose Estimation from Smartwatch IMU](https://mlsanity.com/paper/2609.08806/) (2026)
- [One Sensor, Whole Body - 3D Body Pose from a Single Consumer Earbud IMU](https://mlsanity.com/paper/2609.34978/) (2026)
- [Reliability-Gated Fusion of Consumer Head and Foot IMUs for Lower-Body 3D Pose](https://mlsanity.com/paper/2609.35764/) (2026)
- [FlowAvatar: Real-Time Full-Body Avatars from Sparse Egocentric Inputs on Consumer XR Devices](https://mlsanity.com/paper/2610.16277/) (2026)
- [IMU-Bench: Benchmarking Wrist IMU Representations Across Kinematic, Semantic and Clinical Tasks](https://mlsanity.com/paper/2610.19481/) (2026)
- [Robust Real-Time Monocular Human Pose Estimation with Insole-Based Sensor Fusion](https://mlsanity.com/paper/2610.19494/) (2026)

## Abstract (arXiv)

There has been a continued trend towards minimizing instrumentation for full-body motion capture, going from specialized rooms and equipment, to arrays of worn sensors and recently sparse inertial pose capture methods. However, as these techniques migrate towards lower-fidelity IMUs on ubiquitous commodity devices, like phones, watches, and earbuds, challenges arise including compromised online performance, temporal consistency, and loss of global translation due to sensor noise and drift. Addressing these challenges, we introduce MobilePoser, a real-time system for full-body pose and global translation estimation using any available subset of IMUs already present in these consumer devices. MobilePoser employs a multi-stage deep neural network for kinematic pose estimation followed by a physics-based motion optimizer, achieving state-of-the-art accuracy while remaining lightweight. We conclude with a series of demonstrative applications to illustrate the unique potential of MobilePoser across a variety of fields, such as health and wellness, gaming, and indoor navigation to name a few.