论文标题
D $^{\ bf {3}} $：体育视频中多运动跟踪的重复检测去激光
D$^{\bf{3}}$: Duplicate Detection Decontaminator for Multi-Athlete Tracking in Sports Videos
论文作者
论文摘要
在体育视频中跟踪多个运动员是一项非常具有挑战性的多目标跟踪（MOT）任务，因为运动员通常具有相同的外观，并且彼此之间彼此密切相同，因此使一个常见的遮挡问题成为一个令人讨厌的重复检测。在本文中，重复检测是新的，精确地定义为在同一运动员上通过一帧中的多个检测箱在同一运动员上误导。为了解决这个问题，我们精心设计了一种基于变压器的新型副本检测器（d $^3 $）进行培训，以及用于匹配的特定算法Rally-Hungarian（RH）。一旦重复检测发生，D $^3 $立即通过产生增强框损失来修改过程。由团队运动替代规则触发的RH极为适合运动视频。此外，为了补充没有拍摄更改的跟踪数据集，我们根据名为RallyTrack的体育视频发布了一个新数据集。在RallyTrack上进行了广泛的实验表明，将D $^3 $和RH结合起来，可以通过MOTA中的9.2和4.5在Hota中显着提高跟踪性能。同时，关于Mot系列和Dancetrack的实验发现，D $^3 $可以在训练过程中加速融合，尤其是在MOT17上节省多达80％的原始培训时间。最后，我们的模型仅通过排球视频进行培训，可以直接应用于MAT的篮球和足球视频，这显示了我们方法的优先级。我们的数据集可从https://github.com/heruihr/rallytrack获得。
Tracking multiple athletes in sports videos is a very challenging Multi-Object Tracking (MOT) task, since athletes often have the same appearance and are intimately covered with each other, making a common occlusion problem becomes an abhorrent duplicate detection. In this paper, the duplicate detection is newly and precisely defined as occlusion misreporting on the same athlete by multiple detection boxes in one frame. To address this problem, we meticulously design a novel transformer-based Duplicate Detection Decontaminator (D$^3$) for training, and a specific algorithm Rally-Hungarian (RH) for matching. Once duplicate detection occurs, D$^3$ immediately modifies the procedure by generating enhanced boxes losses. RH, triggered by the team sports substitution rules, is exceedingly suitable for sports videos. Moreover, to complement the tracking dataset that without shot changes, we release a new dataset based on sports video named RallyTrack. Extensive experiments on RallyTrack show that combining D$^3$ and RH can dramatically improve the tracking performance with 9.2 in MOTA and 4.5 in HOTA. Meanwhile, experiments on MOT-series and DanceTrack discover that D$^3$ can accelerate convergence during training, especially save up to 80 percent of the original training time on MOT17. Finally, our model, which is trained only with volleyball videos, can be applied directly to basketball and soccer videos for MAT, which shows priority of our method. Our dataset is available at https://github.com/heruihr/rallytrack.
