  Sports analysis and viewing play a pivotal role in the current sports domain,
offering significant value not only to coaches and athletes but also to fans
and the media. In recent years, the rapid development of virtual reality (VR)
and augmented reality (AR) technologies have introduced a new platform for
watching games. Visualization of sports competitions in VR/AR represents a
revolutionary technology, providing audiences with a novel immersive viewing
experience. However, there is still a lack of related research in this area. In
this work, we present for the first time a comprehensive system for sports
competition analysis and real-time visualization on VR/AR platforms. First, we
utilize multiview LiDARs and cameras to collect multimodal game data.
Subsequently, we propose a framework for multi-player tracking and pose
estimation based on a limited amount of supervised data, which extracts precise
player positions and movements from point clouds and images. Moreover, we
perform avatar modeling of players to obtain their 3D models. Ultimately, using
these 3D player data, we conduct competition analysis and real-time
visualization on VR/AR. Extensive quantitative experiments demonstrate the
accuracy and robustness of our multi-player tracking and pose estimation
framework. The visualization results showcase the immense potential of our
sports visualization system on the domain of watching games on VR/AR devices.
The multimodal competition dataset we collected and all related code will be
released soon.
