用事件相机实时定位网球击球点,解决高帧率捕捉难题
Locating Tennis Ball Impact on the Racket in Real Time Using an Event Camera
- 结合事件相机与原创算法,通过亮度变化时间对称性检测击球瞬间
- 实验结果在运动员表现测量允许误差范围内,计算延迟满足实时需求
- 适合需要长期连续监测击球数据的训练分析场景
在网球等球拍类运动中,精准定位球拍击球位置有助于揭示球员与装备特性,推动个性化装备设计。传统方法依赖高速摄像机测量击球点,但其内存消耗大,难以长时间拍摄,且人工标注位置耗时易错,限制了完整比赛场景的采集,影响性能分析。本文提出一种基于事件相机的实时击球点定位方法。事件相机以微秒级精度捕捉亮度变化(称为“事件”),在高速运动下仍保持低内存占用,支持长时间连续监控。方法包含三个识别步骤:挥拍时间范围、击球时刻判定、球与球拍轮廓提取。采用常规计算机视觉技术结合原创事件处理算法,通过检测时间对称性中的极性不对称性(PATS)实现击球时刻精准识别。实验结果符合运动员表现测量允许误差范围,且计算耗时足够支持实时应用。
原文摘要 · Abstract (English)
In racket sports, such as tennis, locating the ball's position at impact is important in clarifying player and equipment characteristics, thereby aiding in personalized equipment design. High-speed cameras are used to measure the impact location; however, their excessive memory consumption limits prolonged scene capture, and manual digitization for position detection is time-consuming and prone to human error. These limitations make it difficult to effectively capture the entire playing scene, hindering the ability to analyze the player's performance. We propose a method for locating the tennis ball impact on the racket in real time using an event camera. Event cameras efficiently measure brightness changes (called `events') with microsecond accuracy under high-speed motion while using lower memory consumption. These cameras enable users to continuously monitor their performance over extended periods. Our method consists of three identification steps: time range of swing, timing at impact, and contours of ball and racket. Conventional computer vision techniques are utilized along with an original event-based processing to detect the timing at impact (PATS: the amount of polarity asymmetry in time symmetry). The results of the experiments were within the permissible range for measuring tennis players' performance. Moreover, the computation time was sufficiently short for real-time applications.
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