Monocular human pose estimation: A survey of deep learning-based methods

Vision-based monocular human pose estimation, as one of the most fundamental and challenging problems in computer vision, aims to obtain posture of the human body from input images or video sequences. The recent developments of deep learning techniques have been brought significant progress and rema...

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Bibliographic Details
Published in:Computer vision and image understanding Vol. 192; p. 102897
Main Authors: Chen, Yucheng, Tian, Yingli, He, Mingyi
Format: Journal Article
Language:English
Published: Elsevier Inc 01.03.2020
Subjects:
Deep learning
Human pose estimation
Survey
Deep learning
Survey
Human pose estimation
41A10
65D05
65D17
41A05
ISSN:1077-3142, 1090-235X
Online Access:Get full text
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Summary:Vision-based monocular human pose estimation, as one of the most fundamental and challenging problems in computer vision, aims to obtain posture of the human body from input images or video sequences. The recent developments of deep learning techniques have been brought significant progress and remarkable breakthroughs in the field of human pose estimation. This survey extensively reviews the recent deep learning-based 2D and 3D human pose estimation methods published since 2014. This paper summarizes the challenges, main frameworks, benchmark datasets, evaluation metrics, performance comparison, and discusses some promising future research directions.
ISSN:1077-3142
1090-235X
DOI:10.1016/j.cviu.2019.102897