二维人体姿态估计研究综述

A Survey of Two Dimension Human Pose Estimation

人体姿态估计一直是计算机视觉中一个备受关注的研究热点,在智能安防、人机交互、动作识别等领域有着重要的研究价值。近年来,随着深度学习技术的快速发展,人体姿态估计效果不断提升,已经开始广泛应用于计算机视觉的相关领域。梳理二维人体姿态估计算法的发展与现状,总结传统算法与基于深度学习的姿态估计算法的发展与改进,并做出对比;讨论二维人体姿态估计所面临的困难与挑战,并对未来的发展方向做出展望。

Human pose estimation has always been a hot research topic in computer vision, which has critical research value in the field of intelligent security, human-computer interaction, motion recognition and so on. In recent years, the accuracy of human pose estimation is greatly improved with deep learning, thus the human pose estimation has been widely used in many fields. The development and present situation of the two-dimension human pose estimation methods are reviewed. Firstly, summarizes the development and improvement of the traditional algorithms and deep learning-based algorithms, and then compares them. Finally, discusses the difficulties and challenges of the two-dimension human pose estimation, and prospects the future development direction.