Recent advances in computer vision and deep learning have influenced the field of sports performance analysis for researchers to track and reconstruct freely moving humans without any marker attachment. However, there are few works for vision-based motion capture and intelligent analysis for professional TaiChi movement. In this paper, we propose a framework for TaiChi performance capture and analysis with multi-view geometry and artificial intelligence technology. The main innovative work is as follows: 1) A multi-camera system suitable for TaiChi motion capture is built and the multi-view TaiChi data is collected and processed; 2) A combination of traditional visual method and implicit neural radiance field is proposed to achieve sparse 3D skeleton fusion and dense 3D surface reconstruction. 3) The normalization modeling of movement sequences is carried out based on motion transfer, so as to realize TaiChi performance analysis for different groups. We have carried out evaluation experiments, and the experimental results have shown the efficiency of our method.

翻译：近年来，计算机视觉与深度学习的进展推动了运动性能分析领域的研究，使研究人员能够无需任何标记物即可追踪并重建自由运动的人体。然而，针对专业太极拳动作的基于视觉的运动捕捉与智能分析研究仍较为稀缺。本文提出了一套融合多视角几何与人工智能技术的太极拳表演捕捉与分析框架，主要创新工作包括：1）构建适用于太极拳运动捕捉的多摄像机系统，完成多视角太极拳数据的采集与处理；2）提出传统视觉方法与隐式神经辐射场相结合的技术，实现稀疏三维骨架融合与稠密三维表面重建；3）基于运动迁移对动作序列进行归一化建模，进而实现不同群体的太极拳表演分析。我们开展了评估实验，实验结果证明了本方法的有效性。