论文标题
PosetrackReid：数据集说明
PoseTrackReID: Dataset Description
论文作者
论文摘要
当前的基于视频的人重新识别的数据集（RE-ID）不包括针对感兴趣的人的人类姿势注释的形式的结构知识。尽管如此，姿势信息对于将有用的功能信息从背景或遮挡噪声中删除非常有帮助。尤其是现实世界中的现实情况，例如监视，在人群或障碍中包含许多遮挡。另一方面，基于视频的人重新ID可以使其他任务受益，例如多人姿势跟踪，从可靠的功能匹配来看。因此，我们提出了PoSetrackReid，这是一个用于多人姿势跟踪和基于视频的人重新ID的大型数据集。借助Posetrackreid，我们想弥合人重新ID和多人姿势跟踪之间的差距。此外，该数据集为多帧人重新ID的当前最新方法提供了一个很好的基准。
Current datasets for video-based person re-identification (re-ID) do not include structural knowledge in form of human pose annotations for the persons of interest. Nonetheless, pose information is very helpful to disentangle useful feature information from background or occlusion noise. Especially real-world scenarios, such as surveillance, contain a lot of occlusions in human crowds or by obstacles. On the other hand, video-based person re-ID can benefit other tasks such as multi-person pose tracking in terms of robust feature matching. For that reason, we present PoseTrackReID, a large-scale dataset for multi-person pose tracking and video-based person re-ID. With PoseTrackReID, we want to bridge the gap between person re-ID and multi-person pose tracking. Additionally, this dataset provides a good benchmark for current state-of-the-art methods on multi-frame person re-ID.
