Research on 2D Human Pose Estimation Based on Deep Learning

10.6911/WSRJ.202206_8(6).0007

Xialing Wu；Baorong Zhong

Deep learning ； Human Pose Estimation ； HRNet ； Higher‐HRNet

World Scientific Research Journal

8卷6期（2022 / 06 / 01）

47 - 53

英文

Human pose estimation is one of the basic tasks of computer vision, which can be widely used in action recognition, human‐computer interaction, and so on. Human pose estimation is to locate the position information of human pose joint points through input images or videos. The position of the person's pose in the current state can be estimated. The traditional 2D human pose estimation cannot adapt to the complexity of human joints and the transformation of the environment, so it has great limitations. On the other hand, 2D human pose estimation based on deep learning can achieve accurate joint point positions, and the influence factor of environmental changes is small, so it gets rid of the limitations of traditional methods. In this paper, the bottom‐up Higher‐HRNet algorithm is used to evaluate the human body pose, which can estimate the joint points of the human body when it is occluded.