This is a brief technical report of our proposed method for Multiple-Object Tracking (MOT) Challenge in Complex Environments. In this paper, we treat the MOT task as a two-stage task including human detection and trajectory matching. Specifically, we designed an improved human detector and associated most of detection to guarantee the integrity of the motion trajectory. We also propose a location-wise matching matrix to obtain more accurate trace matching. Without any model merging, our method achieves 66.672 HOTA and 93.971 MOTA on the DanceTrack challenge dataset.
翻译:这是一份关于我们复杂环境中多物体跟踪挑战的拟议方法的简要技术报告。在本文中,我们把MOT任务视为包括人类探测和轨迹匹配在内的两阶段任务。具体地说,我们设计了改进的人体探测器,并将大部分探测结果联系起来,以保证运动轨迹的完整性。我们还提出了一个地点匹配矩阵,以获得更准确的追踪匹配。在没有任何模型合并的情况下,我们的方法在舞蹈轨迹挑战数据集上实现了66 672 HOTA和93.971 META。