A comparative study on preprocessing methods for object tracking in sports events

Abstract

Due to the development of machine learning, interest in automatic recognition of objects in videos is increasing. In the sports field, there is a growing demand for a technology for automatically recognizing and tracking various objects in a sports game video. However, it is very difficult to recognize and track an object without proper preprocessing due to its small size and large sports field. In this paper, we compare background substraction and edge detection, which are typical preprocessing methods for automatic recognition and tracking of objects in sports images, and analyze advantages and disadvantages of each method.