Visualizing Skiers' Trajectories in Monocular Videos
This is an incremental solution for enhancing training and broadcasting in alpine skiing by analyzing trajectories from video data.
The paper tackles the problem of visualizing skiers' trajectories from monocular videos, proposing SkiTraVis to separate skier and camera motion, with experiments on professional competition videos showing potential for broadcasting and coaching.
Trajectories are fundamental to winning in alpine skiing. Tools enabling the analysis of such curves can enhance the training activity and enrich broadcasting content. In this paper, we propose SkiTraVis, an algorithm to visualize the sequence of points traversed by a skier during its performance. SkiTraVis works on monocular videos and constitutes a pipeline of a visual tracker to model the skier's motion and of a frame correspondence module to estimate the camera's motion. The separation of the two motions enables the visualization of the trajectory according to the moving camera's perspective. We performed experiments on videos of real-world professional competitions to quantify the visualization error, the computational efficiency, as well as the applicability. Overall, the results achieved demonstrate the potential of our solution for broadcasting media enhancement and coach assistance.