Multi-target Multi-camera Tracking (MTMCT) aims to extract the trajectories from videos captured by a set of cameras. Recently, the tracking performance of MTMCT is significantly enhanced with the employment of re-identification (Re-ID) model. However, the appearance feature usually becomes unreliable due to the occlusion and orientation variance of the targets. Directly applying Re-ID model in MTMCT will encounter the problem of identity switches (IDS) and tracklet fragment caused by occlusion. To solve these problems, we propose a novel tracking framework in this paper. In this framework, the occlusion status and orientation information are utilized in Re-ID model with human pose information considered. In addition, the tracklet association using the proposed fused tracking feature is adopted to handle the fragment problem. The proposed tracker achieves 81.3\% IDF1 on the multiple-camera hard sequence, which outperforms all other reference methods by a large margin.

本文提出了一种新的多目标多摄像机跟踪框架，利用重识别模型，结合遮挡情况、目标朝向以及人体姿态信息，采用融合后的跟踪特征进行跟踪关联，有效地处理了目标识别和跟踪断点问题，并在多摄像机难度序列中取得了优秀的性能。

多目标多摄像头跟踪中的态势感知重新识别特征