Visualizing expert motion for guidance in a VR ski simulator

While humans are quite good at copying motions from others, it is difficult to do so in a dynamic sport such as skiing. Hence, we propose a virtual reality ski training system, which visualizes prerecorded expert motion in different ways and enables users to learn by copying. The system is based on a commercial indoor ski simulator, a VR headset, and two VR trackers to capture the ski's motion. Users can control their skis on the virtual ski slope and improve their skills by following a digital avatar of the expert skier replayed in front of them. We investigate 3 types of visualizations for training: Graphs to visualize the angle of feet compared to the expert, periodic copies of the expert's pose to show the spatial and temporal motion of the key movements, and a more minimal ribbon-trace of the leading skier to point out the optimized trajectory.