论文标题
朝着具有部分游泳池视图的图像中的图像中的自动点检测
Towards Automated Key-Point Detection in Images with Partial Pool View
论文作者
论文摘要
体育分析一直是职业体育组织和学术机构之间的一个新兴领域。随着运动员数据的叛乱和收集，这种分析的主要目标是以可衡量和可量化的方式提高运动员的表现。这项工作旨在减轻足够的游泳数据收集中遇到的一些挑战。过去在这一主题上的工作表明，游泳者的检测和跟踪是可行的，但并非没有挑战。这些挑战包括池定位和确定游泳者相对于池的相对位置。这项工作为解决这些挑战提供了两项贡献。首先，我们提出了一个与游泳分析相关的池模型。其次，我们研究了具有部分游泳池视图的图像中此类关键点的可检测性，这在游泳比赛视频中既具有挑战性又很普遍。
Sports analytics has been an up-and-coming field of research among professional sporting organizations and academic institutions alike. With the insurgence and collection of athlete data, the primary goal of such analysis is to improve athletes' performance in a measurable and quantifiable manner. This work is aimed at alleviating some of the challenges encountered in the collection of adequate swimming data. Past works on this subject have shown that the detection and tracking of swimmers is feasible, but not without challenges. Among these challenges are pool localization and determining the relative positions of the swimmers relative to the pool. This work presents two contributions towards solving these challenges. First, we present a pool model with invariant key-points relevant for swimming analytics. Second, we study the detectability of such key-points in images with partial pool view, which are challenging but also quite common in swimming race videos.
