摘要
近年来,随着深度学习技术的发展,基于深度学习的2D人体姿态估计展现出了极其优异的效果。文章主要对2014年以来基于深度学习的2D人体姿态估计相关内容进行了分析和评述,包括对主流方法的介绍和对数据集评价指标的总结对比,最后还讨论了2D人体姿态估计的未来研究方向。
In recent years,with the development of deep learning technology,2D human pose estimation based on deep learning has shown excellent results.This paper mainly describes the relevant content of 2D human pose estimation based on deep learning since 2014,including the introduction of mainstream methods and the summary and comparison of dataset evaluation indicators,and finally looks forward to the future of human pose estimation based on our own understanding.
作者
任肖月
王俊英
陈晗晗
REN Xiaoyue;WANG Junying;CHEN Hanhan(Hubei Key Laboratory of Intelligent Vision Based Monitoring for Hydroelectric Engineering,China Three Gorges University,Yichang 443002,China;Hubei Province Engineering Research Center for Building Quality Inspection Equipment,Three Gorges University,Yichang 443002,China;College of Computer and Information Technology,China Three Gorges University,Hubei,Yichang 443002,China)
出处
《长江信息通信》
2024年第1期40-43,47,共5页
Changjiang Information & Communications
关键词
人体姿态估计
深度学习
关键点检测
神经网络
human position estimation
deep learning
joints detection
neural networks
