吉林大学学报（信息科学版）2025，Vol.43Issue(5)：1051-1057,7.
基于轻量化高分辨率网络的人体姿态估计方法
Human Pose Estimation Method Based on Improved High-Resolution Network
摘要
Abstract
The accuracy of the existing estimation methods of human pose in the motion evaluation scene needs to be further improved.The methods rely on high-performance computing devices,and the reasoning speed on edge computing devices needs to be further enhanced.Therefore,improvement is made to the classic high-resolution network model to solve the problem of low real-time performance of the existing human pose estimation methods.To address the frequent occlusion issues in motion evaluation scene,random erasure enhancement is applied to the images in the dataset.After experimental comparison and verification,the improved method significantly reduces the number of model parameters and improves the inference speed of the model while ensuring the accuracy of attitude estimation.The algorithm exhibits stronger robustness for occlusion problems,and the improved method can meet the needs of motion evaluation scenarios.关键词
人体姿态估计/高分辨率网络/轻量化/遮挡Key words
human pose estimation/high-resolution network(HRNet)/lightweight/occlusion分类
计算机与自动化引用本文复制引用
张耀平,李井泉,裘昌利,石静苑,汤艳坤,陈大川..基于轻量化高分辨率网络的人体姿态估计方法[J].吉林大学学报（信息科学版）,2025,43(5):1051-1057,7.基金项目
吉林省教育厅科学技术研究基金资助项目(JJKH20231336CY) （JJKH20231336CY）
空军装备综合研究基金资助项目(KJ2021C0120003) （KJ2021C0120003）
