Video-Based Reconstruction of the Trajectories Performed by Skiers

• URL: http://arxiv.org/abs/2112.09647v1
• Date: Fri, 17 Dec 2021 17:40:06 GMT
• Title: Video-Based Reconstruction of the Trajectories Performed by Skiers
• Authors: Matteo Dunnhofer, Alberto Zurini, Maurizio Dunnhofer, Christian Micheloni
• Abstract summary: We propose a video-based approach to reconstruct the sequence of points traversed by an athlete during its performance. Our prototype is constituted by a pipeline of deep learning-based algorithms to reconstruct the athlete's motion and to visualize it according to the camera perspective.
• Score: 14.572756832049285
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Trajectories are fundamental in different skiing disciplines. Tools enabling the analysis of such curves can enhance the training activity and enrich the broadcasting contents. However, the solutions currently available are based on geo-localized sensors and surface models. In this short paper, we propose a video-based approach to reconstruct the sequence of points traversed by an athlete during its performance. Our prototype is constituted by a pipeline of deep learning-based algorithms to reconstruct the athlete's motion and to visualize it according to the camera perspective. This is achieved for different skiing disciplines in the wild without any camera calibration. We tested our solution on broadcast and smartphone-captured videos of alpine skiing and ski jumping professional competitions. The qualitative results achieved show the potential of our solution.

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