Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 4
1230-1233,1243

Hand pose estimation using pseudo-3D convolutional neural network

Zhang Hongyuan1
Yuan Jiazheng2
Liu Hongzhe1
Yuan Chunfeng3
Wang Xueqiao1
Deng Zhifang1
1. Beijing Key Laboratory of Information Service Engineering, Beijing Union University, Beijing 100101, China
2. Beijing Open University, Beijing 100081, China
3. National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
DOI: 10.19734/j.issn.1001-3695.2018.09.0772

Abstract

Most of the existing deep learning-based methods for hand pose estimation use a standard three-dimension convolutional neural network(3D CNN) to extract 3D features and estimate the 3D coordinates of hand joints. The features extracted by these methods lack the multi-scale information of the hand, which limits the accuracy of hand pose estimation. In addition, due to the huge computational cost and memory requirements of the 3D CNN, these methods are often difficult to meet the real-time requirement. To overcome these weaknesses, the proposed method used a spatial filter and a depth filter to simulate 3D convolutions, which reduced the amount of parameters. It extracted and integrates features at various scales, making full use of the 3D information of hand pose. Experiments show that this method can improve estimation accuracy, reduce model size, and run at over 119 fps on a standard computer with a single GPU.

Foundation Support

国家自然科学基金资助项目(61571045)
北京成像技术高精尖创新中心项目(BAICIT-2016002)
北京市教委科技计划一般项目(KM201811417002)
北京联合大学研究生资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.09.0772
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 4
Section: Technology of Graphic & Image
Pages: 1230-1233,1243
Serial Number: 1001-3695(2020)04-058-1230-04

Publish History

[2020-04-05] Printed Article

Cite This Article

张宏源, 袁家政, 刘宏哲, 等. 基于伪三维卷积神经网络的手势姿态估计 [J]. 计算机应用研究, 2020, 37 (4): 1230-1233,1243. (Zhang Hongyuan, Yuan Jiazheng, Liu Hongzhe, et al. Hand pose estimation using pseudo-3D convolutional neural network [J]. Application Research of Computers, 2020, 37 (4): 1230-1233,1243. )

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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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