Abstract
Multi-object tracking in broadcast soccer is difficult because occlusions, scale changes, and crowded interactions frequently disrupt identity continuity. This paper proposes a detector-anchored SAM2 policy that periodically re-aligns propagated tracks with detector outputs to improve trajectory consistency. We benchmark six detector-tracker combinations on SoccerNet-Tracking by pairing two RF-DETR variants with ByteTrack, BoT-SORT, and SAM2, all evaluated under a common protocol. On the full 49-sequence test split, RF-DETR Base + detector-anchored SAM2 achieves the best HOTA (0.512) and IDF1 (0.614) among the tested variants, while classical trackers retain substantially higher throughput. The results show that detector-anchored segmentation-assisted tracking is a strong option for offline tactical analysis where trajectory continuity matters more than runtime.
Paper Type
Short Paper
DOI
10.62036/ISD.2026.58
Detector-Anchored SAM2 for Trajectory-Consistent Multi-Object Tracking in Broadcast Soccer
Multi-object tracking in broadcast soccer is difficult because occlusions, scale changes, and crowded interactions frequently disrupt identity continuity. This paper proposes a detector-anchored SAM2 policy that periodically re-aligns propagated tracks with detector outputs to improve trajectory consistency. We benchmark six detector-tracker combinations on SoccerNet-Tracking by pairing two RF-DETR variants with ByteTrack, BoT-SORT, and SAM2, all evaluated under a common protocol. On the full 49-sequence test split, RF-DETR Base + detector-anchored SAM2 achieves the best HOTA (0.512) and IDF1 (0.614) among the tested variants, while classical trackers retain substantially higher throughput. The results show that detector-anchored segmentation-assisted tracking is a strong option for offline tactical analysis where trajectory continuity matters more than runtime.
Recommended Citation
Eichner, J., Dyczkowski, K., Górecki, T. & Grzelak, B.(2026). Detector-Anchored SAM2 for Trajectory-Consistent Multi-Object Tracking in Broadcast Soccer. In M. Valenta, B. Mannová, R. Pergl, A. Przybylek, M. Lang, H. Linger, C. Schneider, N. Iivari, & E. Insfran (Eds.), Making ISD Sustainable: Reloaded with AI and Automation (ISD2026 Proceedings). Prague, Czech Republic: Czech Technical University in Prague. ISBN: 978-80-01-07585-2. https://doi.org/10.62036/ISD.2026.58