Technology of Graphic & Image
|
App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 7
2178-2182,2202

ARGP-Pose:3D human pose estimate based on analysis of relationship between joint points and group prediction

Huang Chengyuan1
Song Xiaoning1
Feng Zhenhua2
1. School of Artificial Intelligence & Computer Science, Jiangnan University, Wuxi Jiangsu 214122, China
2. Dept. of Computer Science, University of Surrey, Guildford GU2 7XH, UK
DOI: 10.19734/j.issn.1001-3695.2021.11.0618

Abstract

The research in 3D human pose estimation from 2D images has achieved great success in recent years. However, the performance of existing 3D human pose estimation methods may degrade significantly in complicated scenarios. To improve the accuracy and robustness of 3D human pose estimation in unconstrained scenarios, this paper proposed ARGP-Pose, a monocular 3D pose estimation framework by exploring the relationship between the joint points of a 3D human pose. To be more specific, the proposed method included a new joint point preprocessing method and a 3D pose estimation network. The preprocessing method enhanced structural features and extracted the relationship among joint points, which were used as input of the following pose estimation network. Also, the proposed network fused local information of each joint point and the global information of the overall pose for rich feature extraction. Additionally, the proposed method extracted the temporal information by using a self-attention module, which achieved further performance boost. Last, for a complex human pose, this method decomposed the prediction of the whole pose into the prediction of each point, which again improved the estimation accuracy for human bodies with complex pose variations. The experimental results obtained on several well-known benchmarking datasets, such as Human3.6M and HumanEva-I, demonstrate the merits and superiority of the proposed method.

Foundation Support

国家自然科学基金资助项目(61876072)
江苏省“六大人才高峰项目”(XYDXX-012)
江苏省研究生科研与实践创新计划项目(SJCX20_0776)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.11.0618
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 7
Section: Technology of Graphic & Image
Pages: 2178-2182,2202
Serial Number: 1001-3695(2022)07-042-2178-05

Publish History

[2022-01-18] Accepted Paper
[2022-07-05] Printed Article

Cite This Article

黄程远, 宋晓宁, 冯振华. ARGP-Pose:基于关键点间关系分析与分组预测的3D人体姿态估计 [J]. 计算机应用研究, 2022, 39 (7): 2178-2182,2202. (Huang Chengyuan, Song Xiaoning, Feng Zhenhua. ARGP-Pose:3D human pose estimate based on analysis of relationship between joint points and group prediction [J]. Application Research of Computers, 2022, 39 (7): 2178-2182,2202. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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