Virtual Environments Lab, Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University, Seoul 06974, Korea.
Sensors (Basel). 2021 Mar 27;21(7):2340. doi: 10.3390/s21072340.
Human pose estimation and tracking in real-time from multi-sensor systems is essential for many applications. Combining multiple heterogeneous sensors increases opportunities to improve human motion tracking. Using only a single sensor type, e.g., inertial sensors, human pose estimation accuracy is affected by sensor drift over longer periods. This paper proposes a human motion tracking system using lidar and inertial sensors to estimate 3D human pose in real-time. Human motion tracking includes human detection and estimation of height, skeletal parameters, position, and orientation by fusing lidar and inertial sensor data. Finally, the estimated data are reconstructed on a virtual 3D avatar. The proposed human pose tracking system was developed using open-source platform APIs. Experimental results verified the proposed human position tracking accuracy in real-time and were in good agreement with current multi-sensor systems.
从多传感器系统中实时进行人体姿态估计和跟踪对于许多应用至关重要。结合多个异构传感器可以提高人体运动跟踪的机会。仅使用单一传感器类型，例如惯性传感器，随着时间的推移，人体姿态估计的准确性会受到传感器漂移的影响。本文提出了一种使用激光雷达和惯性传感器的人体运动跟踪系统，用于实时估计 3D 人体姿态。人体运动跟踪包括通过融合激光雷达和惯性传感器数据来检测和估计人体的高度、骨骼参数、位置和方向。最后，将估计的数据重建在虚拟 3D 化身上。所提出的人体姿态跟踪系统是使用开源平台 API 开发的。实验结果验证了所提出的人体位置实时跟踪的准确性，并且与当前的多传感器系统非常吻合。
