Lightweight multi-person motion capture system in the wild
Wenwu Yang, Yue Li, Shuai XING, Jiahang CAI, Xun Wang · Scientia Sinica Informationis · 2023
Markerless multi-person 3D motion capture techniques find applications in various domains such as digital film and animation, 3D games, virtual-real interaction, and human gait analysis. However, most research papers tend to focus on algorithm innovation rather than building an effective motion capture system. In this paper, we present a lightweight motion capture system that uses only sparse multiview cameras for multi-person interactive scenarios. Our algorithm achieves accurate 3D human pose estimation by fully leveraging the complementary information from multiple views and filtering unexpected 2D human joint detections. We set up a lightweight hardware system that enables real-time acquisition, transfer, and effective processing of multiview data. Furthermore, we introduce a modularized parallel processing scheme that facilitates dataflow control. Finally, we achieve a scalable, maintainable, and efficient framework for hardware and software configurations. The experimental results demonstrate the accuracy, effectiveness, and efficiency of our algorithms and the proposed lightweight motion capture system.