中国科学院自动化研究所机构知识库

Tracking soccer players serves as a fundamental prerequisite for the automated analysis of soccer videos. The strides in computer vision technology have paved the way for consistently precise player tracking in soccer videos. However, it's crucial to acknowledge that real-world soccer videos often come with inherent limitations. In response to the practical demand for soccer player tracking, we propose a comprehensive pipeline. For practicality and validity of data analysis, our pipeline includes the main method and the preprocessing process; The main method is to get valid tracking data and to further apply the data, including tracking soccer players based on the attention mechanism, which we call Soccer Player TrackFormer, correction and two-dimensional mapping. The preprocessing process is to handle video concatenation and dataset creation for the sake of making up for the lack of a full-field soccer video dataset. Experiments validate that our method can reliably obtain precise tracking data, significantly augmenting the value of soccer video analysis.