While camera-based capture systems remain the gold standard for recording human motion, learning-based tracking systems based on sparse wearable sensors are gaining popularity. Most commonly, they use inertial sensors, whose propensity for drift and jitter have so far limited tracking accuracy. In this paper, we propose Ultra Inertial Poser, a novel 3D full body pose estimation method that constrains drift and jitter in inertial tracking via inter-sensor distances. We estimate these distances across sparse sensor setups using a lightweight embedded tracker that augments inexpensive off-the-shelf 6D inertial measurement units with ultra-wideband radio-based ranging$-$dynamically and without the need for stationary reference anchors. Our method then fuses these inter-sensor distances with the 3D states estimated from each sensor Our graph-based machine learning model processes the 3D states and distances to estimate a person's 3D full body pose and translation. To train our model, we synthesize inertial measurements and distance estimates from the motion capture database AMASS. For evaluation, we contribute a novel motion dataset of 10 participants who performed 25 motion types, captured by 6 wearable IMU+UWB trackers and an optical motion capture system, totaling 200 minutes of synchronized sensor data (UIP-DB). Our extensive experiments show state-of-the-art performance for our method over PIP and TIP, reducing position error from $13.62$ to $10.65cm$ ($22\%$ better) and lowering jitter from $1.56$ to $0.055km/s^3$ (a reduction of $97\%$).

翻译：尽管基于摄像头的捕捉系统仍是记录人体运动的标准方法，基于稀疏可穿戴传感器的学习型追踪系统正日益普及。这类系统通常采用惯性传感器，但其固有的漂移与抖动问题限制了追踪精度。本文提出超惯性定位器（Ultra Inertial Poser），一种新型三维全身姿态估计方法，通过传感器间距离约束惯性追踪中的漂移与抖动。我们利用轻量级嵌入式追踪器估算稀疏传感器布局下的距离，该追踪器在廉价商用六维惯性测量单元上集成超宽带无线电测距功能，可实现动态测距且无需固定参考锚点。随后，我们的方法将传感器间距离与各传感器估计的三维状态融合。基于图结构的机器学习模型处理三维状态与距离数据，估算人体的三维全身姿态与平移量。为训练模型，我们从运动捕捉数据库AMASS中合成惯性测量值与距离估计值。为评估性能，我们贡献了一个包含10名受试者执行25种运动类型的新型运动数据集，由6个可穿戴IMU+UWB追踪器与光学运动捕捉系统同步采集，总计200分钟同步传感器数据（UIP-DB）。广泛实验表明，本方法在PIP与TIP基础上达到最优性能，位置误差从13.62厘米降至10.65厘米（提升22%），抖动从1.56 km/s³降至0.055 km/s³（降低97%）。