Visualizing skiers' trajectories in monocular videos

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.
© Copyright 2023 Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. Published by IEEE. All rights reserved.

Bibliographic Details
Subjects:
Notations:endurance sports technical and natural sciences
Tagging:Algorithmus
Published in:Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops
Language:English
Published: Piscataway, NJ IEEE 2023
Online Access:https://openaccess.thecvf.com/content/CVPR2023W/CVSports/html/Dunnhofer_Visualizing_Skiers_Trajectories_in_Monocular_Videos_CVPRW_2023_paper.html
Pages:5188-5198
Document types:article
Level:advanced