论文标题
SMOT：单发多对象跟踪
SMOT: Single-Shot Multi Object Tracking
论文作者
论文摘要
我们提出了单杆多对象跟踪器（SMOT），这是一个新的跟踪框架，将任何单杆检测器（SSD）模型转换为在线多个对象跟踪器，该模型强调同时检测和跟踪对象路径。与遇到对象探测器犯错的检测方法的现有跟踪相反，SMOT采用了最近提出的通过重新检测的跟踪方案。我们通过提出一个新颖的跟踪锚分配模块将该方案与SSD检测器结合起来。使用此设计，Smot能够以恒定的人均运行时生成轨迹。然后使用轻加权的链接算法用于在线曲目链接。在对象跟踪的三个基准下：汉娜，音乐视频和MOT17，拟议中的SMOT实现了最先进的性能。
We present single-shot multi-object tracker (SMOT), a new tracking framework that converts any single-shot detector (SSD) model into an online multiple object tracker, which emphasizes simultaneously detecting and tracking of the object paths. Contrary to the existing tracking by detection approaches which suffer from errors made by the object detectors, SMOT adopts the recently proposed scheme of tracking by re-detection. We combine this scheme with SSD detectors by proposing a novel tracking anchor assignment module. With this design SMOT is able to generate tracklets with a constant per-frame runtime. A light-weighted linkage algorithm is then used for online tracklet linking. On three benchmarks of object tracking: Hannah, Music Videos, and MOT17, the proposed SMOT achieves state-of-the-art performance.
