BaroPoser: Real-time Human Motion Tracking from IMUs and Barometers in Everyday Devices

TL;DR

BaroPoser is a real-time human motion tracking method that combines IMU and barometric data from everyday devices to improve pose estimation and global translation, especially on uneven terrain.

Contribution

It introduces a novel approach that integrates barometric data with IMUs for enhanced human pose and translation estimation in real time.

Findings

Outperforms state-of-the-art IMU-only methods on benchmark datasets.

Effectively estimates pose and translation on uneven terrain.

Demonstrates real-time capability on standard smartphones and smartwatches.

Abstract

In recent years, tracking human motion using IMUs from everyday devices such as smartphones and smartwatches has gained increasing popularity. However, due to the sparsity of sensor measurements and the lack of datasets capturing human motion over uneven terrain, existing methods often struggle with pose estimation accuracy and are typically limited to recovering movements on flat terrain only. To this end, we present BaroPoser, the first method that combines IMU and barometric data recorded by a smartphone and a smartwatch to estimate human pose and global translation in real time. By leveraging barometric readings, we estimate sensor height changes, which provide valuable cues for both improving the accuracy of human pose estimation and predicting global translation on non-flat terrain. Furthermore, we propose a local thigh coordinate frame to disentangle local and global motion input for better pose representation learning. We evaluate our method on both public benchmark datasets and real-world recordings. Quantitative and qualitative results demonstrate that our approach outperforms the state-of-the-art (SOTA) methods that use IMUs only with the same hardware configuration.