Team-Aware Football Player Tracking with SAM: An Appearance-Based Approach to Occlusion Recovery

• URL: http://arxiv.org/abs/2512.08467v1
• Date: Tue, 09 Dec 2025 10:40:17 GMT
• Title: Team-Aware Football Player Tracking with SAM: An Appearance-Based Approach to Occlusion Recovery
• Abstract summary: This paper presents a lightweight SAM-based tracking method for football players.<n>The method combines CSRT trackers and jersey color-based appearance models.<n>Experiments on football video sequences show that the approach achieves 7.6-7.7 FPS with stable memory usage.
• Score: 1.2461503242570642
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Football player tracking is challenged by frequent occlusions, similar appearances, and rapid motion in crowded scenes. This paper presents a lightweight SAM-based tracking method combining the Segment Anything Model (SAM) with CSRT trackers and jersey color-based appearance models. We propose a team-aware tracking system that uses SAM for precise initialization and HSV histogram-based re-identification to improve occlusion recovery. Our evaluation measures three dimensions: processing speed (FPS and memory), tracking accuracy (success rate and box stability), and robustness (occlusion recovery and identity consistency). Experiments on football video sequences show that the approach achieves 7.6-7.7 FPS with stable memory usage (~1880 MB), maintaining 100 percent tracking success in light occlusions and 90 percent in crowded penalty-box scenarios with 5 or more players. Appearance-based re-identification recovers 50 percent of heavy occlusions, demonstrating the value of domain-specific cues. Analysis reveals key trade-offs: the SAM + CSRT combination provides consistent performance across crowd densities but struggles with long-term occlusions where players leave the frame, achieving only 8.66 percent re-acquisition success. These results offer practical guidelines for deploying football tracking systems under resource constraints, showing that classical tracker-based methods work well with continuous visibility but require stronger re-identification mechanisms for extended absences.

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