We propose a Cascaded Buffered IoU (C-BIoU) tracker to track multiple objects that have irregular motions and indistinguishable appearances. When appearance features are unreliable and geometric features are confused by irregular motions, applying conventional Multiple Object Tracking (MOT) methods may generate unsatisfactory results. To address this issue, our C-BIoU tracker adds buffers to expand the matching space of detections and tracks, which mitigates the effect of irregular motions in two aspects: one is to directly match identical but non-overlapping detections and tracks in adjacent frames, and the other is to compensate for the motion estimation bias in the matching space. In addition, to reduce the risk of overexpansion of the matching space, cascaded matching is employed: first matching alive tracks and detections with a small buffer, and then matching unmatched tracks and detections with a large buffer. Despite its simplicity, our C-BIoU tracker works surprisingly well and achieves state-of-the-art results on MOT datasets that focus on irregular motions and indistinguishable appearances. Moreover, the C-BIoU tracker is the dominant component for our 2-nd place solution in the CVPR'22 SoccerNet MOT and ECCV'22 MOTComplex DanceTrack challenges. Finally, we analyze the limitation of our C-BIoU tracker in ablation studies and discuss its application scope.

翻译：我们提出了一种级联缓冲交并比（C-BIoU）追踪器，用于追踪具有不规则运动与难以区分外观的多目标。当外观特征不可靠且几何特征因不规则运动而混淆时，传统多目标追踪（MOT）方法可能产生不理想的结果。针对此问题，我们的C-BIoU追踪器通过添加缓冲区域扩展检测与轨迹的匹配空间，从两方面减轻不规则运动的影响：一是直接匹配相邻帧中相同但无重叠的检测与轨迹，二是在匹配空间中补偿运动估计偏差。此外，为降低匹配空间过度扩展的风险，采用级联匹配策略：首先使用小缓冲区域匹配活跃轨迹与检测，随后使用大缓冲区域匹配未匹配的轨迹与检测。尽管方法简洁，C-BIoU追踪器表现优异，在聚焦不规则运动与外观相似性的MOT数据集上达到当前最优水平。同时，该追踪器也是我们在CVPR'22 SoccerNet MOT与ECCV'22 MOTComplex DanceTrack挑战赛中取得亚军的核心组件。最后，我们通过消融实验分析了C-BIoU追踪器的局限性，并讨论了其适用范围。