电子器件2024，Vol.47Issue(4)：1133-1140,8.DOI:10.3969/j.issn.1005-9490.2024.04.040
基于改进高分辨率网络的三维人体姿态估计方法
3D Human Pose Estimation Method Based on Improved High Resolution Network
摘要
Abstract
In order to solve the problems of occlusion and human key point movement under complex background in real scenes,a top-down two-stage human pose estimation method is proposed.Firstly,the improved YOLO and SORT are used for two-dimensional human de-tection and tracking,and the YOLOv3 network structure,loss function and prior frame size are improved to enhance the network detection ability and feature expression ability,and improve the applicability and accuracy of human target detection.Secondly,HRNet integrated with attention mechanism is used for 2D attitude estimation,and the original residual module is featured to enhance the cross-channel in-formation exchange between multi-layer features at different scales and improve the recognition effect of blocked key points.Finally,GAST-NET is used to generate 3D posture.The experimental results show that mean per joint position error and procrustes analysis mean per joint position error are 45.0 mm and 35.4 mm respectively.Under the condition of serious occlusion,the accurate position of human key points can still be obtained.关键词
姿态估计/多尺度特征融合/注意力机制/三维关键点Key words
attitude estimation/multi-scale feature fusion/attention mechanism/3D key points分类
信息技术与安全科学引用本文复制引用
闻举,伊力哈木·亚尔买买提..基于改进高分辨率网络的三维人体姿态估计方法[J].电子器件,2024,47(4):1133-1140,8.基金项目
国家自然科学基金项目(61866037,61462082) （61866037,61462082）
