用单目摄像头和姿态识别估算运动员步长，无需标记物
Markerless Stride Length estimation in Athletic using Pose Estimation with monocular vision
- 结合霍夫变换与人体姿态检测定位跑者腿部关节
- 通过仿射变换计算步长，实验验证准确率高
- 适合体育教练实时分析运动员步态，辅助训练
跑步中的步长和速度变化等表现指标，传统上依赖计步数或赛道标记进行测量。本文提出一种基于计算机视觉的方法，从视频序列中估计步长与速度变化，支持运动员个体化训练评估。通过概率霍夫变换与人体姿态检测算法，精准定位跑者腿部关键点，再利用仿射变换实现步长估算。在三名不同运动员的多段赛跑视频上实验验证，系统表现出良好的实用性与稳定性，具备监测运动员步态参数的潜力，可为教练制定个性化训练计划提供有效工具。
原文摘要 · Abstract (English)
Performance measures such as stride length in athletics and the pace of runners can be estimated using different tricks such as measuring the number of steps divided by the running length or helping with markers printed on the track. Monitoring individual performance is essential for supporting staff coaches in establishing a proper training schedule for each athlete. The aim of this paper is to investigate a computer vision-based approach for estimating stride length and speed transition from video sequences and assessing video analysis processing among athletes. Using some well-known image processing methodologies such as probabilistic hough transform combined with a human pose detection algorithm, we estimate the leg joint position of runners. In this way, applying a homography transformation, we can estimate the runner stride length. Experiments on various race videos with three different runners demonstrated that the proposed system represents a useful tool for coaching and training. This suggests its potential value in measuring and monitoring the gait parameters of athletes.
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