通过姿势估计从单摄像机转播镜头中识别守门员移动时机:试点研究

Chethan Reddy, Woohyoung Jeon
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引用次数: 0

摘要

本研究探讨了如何利用开源姿势估计来识别足球点球过程中的门将扑球动作。本研究的目的是为识别门将俯冲启动提供一种易用、低成本的启发式方法。本研究使用了 2022 年国际足联男子世界杯期间所有 41 次点球大战的单摄像机广播录像(1080p 分辨率,每秒 50 帧)。我们对每个点球进行了分离,并记录了门将起跳和飞行的帧数。然后,我们确定了门柱,创建了一个同构矩阵以考虑摄像机的移动,并通过姿势估计确定了门将的骨骼关键点。根据这些关键点,我们得出了躯干和腿部的正面运动学数据。我们确定了每个运动变量的局部极值,并分离出每个变量在门将飞行前的最后观测极值。通过 OLS 回归,我们发现门将中心点 y 值的最后一个局部极值是预测门将贴标扑救的最强指标,R2 为 0.998,P 值为 0.00。这项研究的结果是初步的,但证明了姿势估计在使用单台摄像机识别现场比赛中特定运动动作计时方面的前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identifying Goalkeeper Movement Timing from Single-Camera Broadcast Footage through Pose Estimation: A Pilot Study
This study explores how open-source pose estimation can be utilized to identify goalkeeper dive initiation during soccer penalty kicks. The purpose of this study is to provide an accessible, low-cost heuristic methodology for identifying goalkeeper dive initiation. This study uses single-camera broadcast footage (1080 p resolution, 50 frames per second) of all 41 penalty shootout kicks attempted during the 2022 FIFA Men’s World Cup. We isolated each penalty kick and recorded the frames of goalkeeper dive initiation and flight. We then identified goalposts to create a homography matrix to account for camera movement and identified the goalkeeper’s skeletal keypoints through pose estimation. From these keypoints, we derived frontal plane kinematics for the torso and legs. We identified local extrema for each kinematic variable and isolated the last observed extrema prior to goalkeeper flight for each variable. Using OLS regression, we found that the last local extremum of the goalkeeper centroid’s y-value was the strongest predictor of labeled commitment to the dive side, with an R2 of 0.998 and a p-value of 0.00. The results of this research are preliminary but demonstrate the promise of pose estimation in identifying sport-specific action timing during live game play using a single camera.
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