A Review of Human Pose Estimation Methods Based on Monocular Vision

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Abstract

This article is a review of the technology methods and industry applications of monocular human pose estimation, which focuses on the recent development of monocular human pose estimation. With the rapid development of computer vision and machine learning, monocular human pose estimation has become a research direction that has attracted much attention. In this article, we first introduce the relevant concepts and significance of monocular human pose estimation, explain the importance of research in this field. Then, we provide a detailed overview of the technical methods of monocular human pose estimation, including two different approaches: monocular 2D human pose estimation and monocular 3D human pose estimation. For each research method, we discuss its principles, development, and pros and cons. Next, we explore the applications of monocular human pose estimation in various fields such as human-computer interaction, autonomous driving, healthcare, and provide examples to highlight the significance of human pose estimation. Finally, we analyze the current research hotspots and challenges and also look forward to the future directions of monocular human pose estimation. This article aims to provide researchers and practitioners with a comprehensive overview and promote the application and further research of monocular human pose estimation technology.

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