High-Speed Object Tracking with Its Application in Golf Playing

This paper presents a new high-speed object tracking algorithm and applies it in tracking high-speed golf balls. Several challenges are encountered in tracking this kind of small-size and high-speed objects; these challenges include: (1) the motion speed (up to 200km/h) of the object is extremely fast that the image captured by the camera can become easily blurred; (2) the size of the objects is small and there is not enough texture feature on the surface of the objects; (3) high-speed objects typically move in outdoor environments, which have complex backgrounds and the light conditions; and (4) a balance between robustness and real-time efficiency is difficult to achieve. There is no existing method can directly solve all these problems. To address these problems, a novel real-time visual tracking algorithm and system are developed that can realize high-speed small object tracking and trajectory predication. The frame difference method was employed to segment the moving objects from the background. The motion blurred object can be detected by applying the proposed object recognition method using multi-features (geometry features and object motion features). Different from the state of the art tracking algorithms, the motion blurring feature was also considered as a feature of the high-speed object, and the tracking robustness of the proposed algorithm does not rely on the texture feature of the tracking objects. To realize real-time efficiency, a region of interest predicting and updating method was proposed that can shrink the processing area of the frames and achieve a high frame rate. Combining visual servoing technology and aerodynamics, the trajectory of the high-speed object can be predicted. The high-speed golf ball tracking experiments were conducted to demonstrate the tracking efficiency and robustness of the algorithm.