A low-cost computer vision system for real-time tennis analysis

Abstract

This paper describes a low-cost vision-based system for real-time tennis game analysis. The system elaborates videos captured by four synchronized and calibrated cameras installed at the sides of the court in order to accurately localize ball and players, and track them in real-time. From this low-level data mid-level events, like shots, bounces, ball in net, and high-level events, like stroke type and line calling, are detected. All this data is made available to the players both on-court during the play or through a web device at the end of the session. Currently, system prototypes are undergoing a field test in three locations in Italy. In addition to positive comments of users, robustness and reliability of the system have been demonstrated with specific evaluation tests. Detection rate of shots is 99.7% while miss detection rate is less than 0.8%. Reliability of the stroke classification is 97.1% and of in/out evaluation is 99.5%. On average reaction time for line calling is 152 ms.