SoccerNet 2023 Tracking Challenge -- 3rd place MOT4MOT Team Technical Report
This work addresses player and ball tracking in soccer videos, which is an incremental improvement for sports analytics applications.
The paper tackled the SoccerNet 2023 tracking challenge by separately detecting and tracking soccer players and the ball, using an online multi-object tracker with post-processing and a fine-tuned YOLOv8l detector, achieving a HOTA score of 66.27 and 3rd place.
The SoccerNet 2023 tracking challenge requires the detection and tracking of soccer players and the ball. In this work, we present our approach to tackle these tasks separately. We employ a state-of-the-art online multi-object tracker and a contemporary object detector for player tracking. To overcome the limitations of our online approach, we incorporate a post-processing stage using interpolation and appearance-free track merging. Additionally, an appearance-based track merging technique is used to handle the termination and creation of tracks far from the image boundaries. Ball tracking is formulated as single object detection, and a fine-tuned YOLOv8l detector with proprietary filtering improves the detection precision. Our method achieves 3rd place on the SoccerNet 2023 tracking challenge with a HOTA score of 66.27.