  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.
