YourSkatingCoach: A Figure Skating Video Benchmark for Fine-Grained Element Analysis
Wei-Yi Chen, Yi-Ling Lin, Yu-An Su, Wei-Hsin Yeh, Lun-Wei Ku

TL;DR
This paper introduces YourSkatingCoach, a comprehensive figure skating dataset with a novel air time detection task, utilizing a Transformer-based model to analyze jump quality and generalize to other sports.
Contribution
It presents a new large-scale figure skating dataset and a Transformer-based approach for fine-grained air time detection, addressing limitations of existing coarse-grained data.
Findings
The proposed model effectively detects jump air time durations.
The dataset enables detailed analysis of figure skating elements.
Cross-sport application shows potential for generalization.
Abstract
Combining sports and machine learning involves leveraging ML algorithms and techniques to extract insight from sports-related data such as player statistics, game footage, and other relevant information. However, datasets related to figure skating in the literature focus primarily on element classification and are currently unavailable or exhibit only limited access, which greatly raise the entry barrier to developing visual sports technology for it. Moreover, when using such data to help athletes improve their skills, we find they are very coarse-grained: they work for learning what an element is, but they are poorly suited to learning whether the element is good or bad. Here we propose air time detection, a novel motion analysis task, the goal of which is to accurately detect the duration of the air time of a jump. We present YourSkatingCoach, a large, novel figure skating dataset…
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Taxonomy
TopicsImage Processing and 3D Reconstruction · Nuclear Physics and Applications · Non-Destructive Testing Techniques
MethodsFocus
