Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 5
1566-1569,1581

Hierarchical target detection and human body attitude estimation based on structured SVM and CNN

Sun Xinling1
Zhang Hao1
Zhao Li2
1. Dept. of Computer Science, Henan Institute of Technology, Xinxiang Henan 453003, China
2. School of Software, Shanxi University, Taiyuan 030013, China
DOI: 10.19734/j.issn.1001-3695.2018.11.0855

Abstract

Aiming at the problem that the existing attitude estimation method cannot accurately extract the feature parameters, this paper proposed a hierarchical model based on structured support vector machine(SSVM) and convolutional neural network(CNN). Firstly, it showed how a SSVM based on the PS component model could be implemented as a two-layer neural network, where the first layer was the convolutional layer and the other layer was the loss-enhanced inference layer. Then, by transforming the structured form of the model into a neural network in the model, the proposed method could simultaneously learn the structural model and the appearance model, and then backpropagated the error to learn the underlying learnable parameters. These parameters could be extracted from the appearance model features. Finally, it transformed the SSVM model into a neural network model, and propagated the error back to the lower layer, and calculated the exact SSVM loss, while learnt the original SSVM by the sub-gradient-based method. Comparing the model with the current advanced recognition model, the results show that the proposed success rate of the hierarchical model is 6% higher than the comparison method and has stronger recognition performance.

Foundation Support

河南省高等学校重点科研项目(19A520019)
山西省基础研究计划项目—青年科技研究基金资助项目(2014021039-6)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.11.0855
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 5
Section: Technology of Graphic & Image
Pages: 1566-1569,1581
Serial Number: 1001-3695(2020)05-059-1566-04

Publish History

[2020-05-05] Printed Article

Cite This Article

孙新领, 张皓, 赵丽. 利用结构化SVM结合CNN的层次化目标检测与人体姿态估计方法 [J]. 计算机应用研究, 2020, 37 (5): 1566-1569,1581. (Sun Xinling, Zhang Hao, Zhao Li. Hierarchical target detection and human body attitude estimation based on structured SVM and CNN [J]. Application Research of Computers, 2020, 37 (5): 1566-1569,1581. )

About the Journal

  • 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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