CVJun 10, 2025

Locating Tennis Ball Impact on the Racket in Real Time Using an Event Camera

arXiv:2506.08327v11 citationsh-index: 2ISACE
Originality Incremental advance
AI Analysis

This work addresses the need for efficient, real-time impact location analysis in racket sports to aid personalized equipment design, though it is incremental as it builds on conventional computer vision with event-based processing.

The paper tackled the problem of locating tennis ball impact on the racket in real time by proposing a method using an event camera, which achieved results within permissible performance measurement ranges and sufficiently short computation time for real-time applications.

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.

Foundations

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