【摘要】 针对多人场景下对单一目标姿态估计的需求，将YOLOv5系列网络与提出的目标选择环节、轻量化light-duc模型进行融合，用于特定目标人体姿态估计。该文利用YOLOv5网络进行人体框检测；将DeepSORT多目标跟踪与条件筛选进行融合，构成目标选择环节用于选出指定目标，设计light-duc轻量化模型，完成指定目标人体姿态估计。实验结果表明，所提light-duc网络与原网络相比，速度提升了157%,YOLOv5s模型与light-duc模型结合对单人视频的检测速度提升了319%。更多还原

【Abstract】 Aiming at the requirement of single person pose estimation in multi-person scene, we combine YOLOv5 series model, object selection and lightweight light-duc model to estimate pose of specific person. YOLOv5 network was used to detect all people in the image. Meanwhile, the object selection composed of DeepSORT multi-object tracking algorithm and criteria-based selection was used to select specific person. The light-duc lightweight network was designed to estimate the pose of specific person. The experimental results show that compared with the original network, the speed of the proposed light-duc network is increased by 157%, combining YOLOv5s with light-duc model, the detection speed of single person video has great improvement, which lead to 319%.更多还原