Abstract
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.
Abstract (translated)
在网球等球拍运动中，确定击球瞬间球的位置对于明确球员和器材特性非常重要，并有助于个性化设备设计。高速相机常用于测量撞击位置；然而，由于其过高的内存消耗限制了长时间场景捕捉的能力，且手动数字化以检测位置耗时长并且容易出现人为错误。这些局限性使得有效捕获整个比赛场面变得困难，从而阻碍了分析球员表现的能力。 我们提出了一种使用事件相机实时定位网球与球拍撞击点的方法。事件相机能够在高速运动中准确地以微秒级精度测量亮度变化（称为“事件”），并且内存消耗较低，使用户能够长时间连续监测其表现。我们的方法包含三个识别步骤：挥拍时间范围、击球时刻以及球和球拍轮廓的确定。 我们采用传统的计算机视觉技术，并结合一种原始的时间对称性中的极性不对称量测法（PATS）来检测击球时间。实验结果显示，测量结果在允许范围内可以准确衡量网球运动员的表现。此外，计算时间对于实时应用来说足够短。
URL
https://arxiv.org/abs/2506.08327
