论文推荐 | 京东发布LightTrack - 自顶向下人体姿态追踪通用框架

京东发布 LightTrack - 自顶向下人体姿态追踪通用框架

推荐理由

这是一篇京东数字科技与匹兹堡大学5月7日公布的论文，现于PoseTrack的Multi Person Pose Tracking排行榜名列第一，在总体MOTA上以微弱优势击败微软的HRNet（尽管在总体AP上仍比HRNet低不少）。

这是迄今第一篇以自顶向下方式完成在线人体姿态追踪的系统。作为一个框架，该工作中的姿态估计部分和ReID部分都是可以灵活替换的。此外，作者还提出了孪生图卷积网络（Siamese Graph Convolution Network）并作为该系统中的Re-ID模块，以图的形式来表示人体关键点，以较低的计算量有效地学习人体姿态的相似度，并对相机的突然移动导致的偏移有较高的鲁棒性。

该工作已于Github开源。代码地址：https://github.com/Guanghan/lighttrack

项目实战

先配置一个conda环境，make一下自带的库，用自带的脚本下载训练好的模型权重和视频，再就是一句python demo_video_mobile.py。后面发现，这个demo读取的是./data/demo/video.mp4文件，我就把它替换成东哥的视频。感觉还挺好玩的~

摘要

In this paper, we propose a novel effective light-weight framework, called as LightTrack, for online human pose tracking. The proposed framework is designed to be generic for top-down pose tracking and is faster than existing online and offline methods. Single-person Pose Tracking (SPT) and Visual Object Tracking (VOT) are incorporated into one unified functioning entity, easily implemented by a replaceable single-person pose estimation module. Our framework unifies single-person pose tracking with multi-person identity association and sheds first light upon bridging keypoint tracking with object tracking. We also propose a Siamese Graph Convolution Network (SGCN) for human pose matching as a Re-ID module in our pose tracking system. In contrary to other Re-ID modules, we use a graphical representation of human joints for matching. The skeletonbased representation effectively captures human pose similarity and is computationally inexpensive. It is robust to sudden camera shift that introduces human drifting. To the best of our knowledge, this is the first paper to propose an online human pose tracking framework in a top-down fashion. The proposed framework is general enough to fit other pose estimators and candidate matching mechanisms. Our method outperforms other online methods while maintaining a much higher frame rate, and is very competitive with our offline state-of-the-art. We make the code publicly available at:https://github.com/Guanghan/lighttrack.

论文链接

https://arxiv.org/pdf/1905.02822.pdf