Recent Advances in 3D Human Pose Estimation: From Optimization to Implementation and Beyond

Author:

Yan Jielu1,Zhou Mingliang2ORCID,Pan Jinli3,Yin Meng4,Fang Bin2

Affiliation:

1. State Key Lab of Internet of Things for Smart City, University of Macau, Taipa, Macau 999078, P. R. China

2. School of Computer Science, Chongqing University, Chongqing 400044, P. R. China

3. TMS Measurement and Control Technology Co., Ltd., P. R. China

4. Chongqing Pharmaceutical Data Information Technology Co., Ltd., Building 3, Block B, Administration Centre, Nanan District, Chongqing, P. R. China

Abstract

3D human pose estimation describes estimating 3D articulation structure of a person from an image or a video. The technology has massive potential because it can enable tracking people and analyzing motion in real time. Recently, much research has been conducted to optimize human pose estimation, but few works have focused on reviewing 3D human pose estimation. In this paper, we offer a comprehensive survey of the state-of-the-art methods for 3D human pose estimation, referred to as pose estimation solutions, implementations on images or videos that contain different numbers of people and advanced 3D human pose estimation techniques. Furthermore, different kinds of algorithms are further subdivided into sub-categories and compared in light of different methodologies. To the best of our knowledge, this is the first such comprehensive survey of the recent progress of 3D human pose estimation and will hopefully facilitate the completion, refinement and applications of 3D human pose estimation.

Funder

Natural Science Foundation of Chongqing

National Natural Science Foundation of China

the Fundamental Research Funds for the Central Universities

Guangxi Key Laboratory of Cryptography and Information Security

Human Resources and Social Security Bureau

Suzhou Institute of USTC

Publisher

World Scientific Pub Co Pte Ltd

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Contextual learning in Video Analytics for Human pose Detection using Bayesian Learning and LSTM;2023 International Conference on Networking and Communications (ICNWC);2023-04-05

2. Automatic translation of sign language with multi-stream 3D CNN and generation of artificial depth maps;Expert Systems with Applications;2023-04

3. Channel Correlation Distillation for Compact Semantic Segmentation;International Journal of Pattern Recognition and Artificial Intelligence;2023-02-20

4. JSL3d: Joint subspace learning with implicit structure supervision for 3D pose estimation;Pattern Recognition;2022-12

5. Temporal-Variation Skeleton Point Correction Algorithm for Improved Accuracy of Human Action Recognition;International Journal of Pattern Recognition and Artificial Intelligence;2022-07-25

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