We introduce a novel motion capture system that reconstructs full-body 3D motion using only sparse pairwise distance (PWD) measurements from body-mounted(UWB) sensors. Using time-of-flight ranging between wireless nodes, our method eliminates the need for external cameras, enabling robust operation in uncontrolled and outdoor environments. Unlike traditional optical or inertial systems, our approach is shape-invariant and resilient to environmental constraints such as lighting and magnetic interference. At the core of our system is Wild-Poser (WiP for short), a compact, real-time Transformer-based architecture that directly predicts 3D joint positions from noisy or corrupted PWD measurements, which can later be used for joint rotation reconstruction via learned methods. WiP generalizes across subjects of varying morphologies, including non-human species, without requiring individual body measurements or shape fitting. Operating in real time, WiP achieves low joint position error and demonstrates accurate 3D motion reconstruction for both human and animal subjects in-the-wild. Our empirical analysis highlights its potential for scalable, low-cost, and general purpose motion capture in real-world settings.

翻译：我们提出了一种新型运动捕捉系统，该系统仅利用身体佩戴超宽带传感器获取的稀疏成对距离测量值，即可重建全身三维运动。通过无线节点间的飞行时间测距技术，我们的方法无需外部摄像头，能够在非受控及户外环境中实现鲁棒运行。与传统光学或惯性系统不同，本方法具有形状不变性，并能抵抗光照及磁场干扰等环境约束。系统的核心是Wild-Poser（简称WiP）——一种基于Transformer的紧凑型实时架构，可直接从含噪声或受损的PWD测量值预测三维关节位置，后续可通过学习方法重建关节旋转。WiP能够泛化至不同形态的主体（包括非人类物种），无需个体身体测量或形状拟合。该系统实时运行时关节位置误差较低，在野外环境中对人类和动物主体均实现了精确的三维运动重建。实证分析表明，本系统在现实场景中具备可扩展、低成本、通用型运动捕捉的应用潜力。