A Survey on Human Pose Estimation. Issue 3 (2nd July 2016)

• Record Type: Journal Article
• Authors: Zhang, Hong-Bo; Lei, Qing; Zhong, Bi-Neng; Du, Ji-Xiang; Peng, JiaLin
• Is Part Of: Intelligent automation & soft computing. Volume 22:Issue 3(2016)
• Page Start: 483
• Page End: 489
• Publication Date: 2016-07-02
• Subjects: Human pose estimation -- depth-based approaches -- traditional image-based methods; Artificial intelligence -- Periodicals; Intelligent control systems -- Periodicals; 003.5
• DOI: 10.1080/10798587.2015.1095419
• Languages: English
• ISSNs: 1079-8587

Abstract

Abstract: Human pose estimation has attracted widespread attention due to its important application value and theoretical significance. A systemic survey of human pose estimation would be very meaningful. However, relevant studies have significantly lagged behind in this respect. To this end, we discuss the difficulties of human pose estimation and give a data-driven overview of recent approaches to performing human pose estimation, including depth-based approaches and traditional image-based methods. While the focus of this study is on approaches using depth and RGB image data, we also discuss human pose estimation methods based on object detection and action recognition. Finally, we give some analysis advice to researchers.