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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 7
2202-2205,2226

Pedestrian detection method based on adaptive feature convolution network

Chen Qiaosong
Gong Panhao
Shen Fahai
Tao Ya
Dong Guangxian
Wang Jin
Deng Xin
Key Laboratory of Data Engineering & Visual Computing, Chongqing University of Posts & Telecommunications, Chongqing 400065, China
DOI: 10.19734/j.issn.1001-3695.2019.02.0032

Abstract

To circumvent the problem of failing to make full use of the shallow features of the convolutional network, this paper improved the existing Faster R-CNN framework and proposed pedestrian detection method based on adaptive feature convolution network, for achieving higher the detection accuracy. This paper has two improvements. Firstly, it designed SFCM module to extract the shallow detail features of the convolution neural network. Secondly, it proposed AFCM module by utilizing the squeeze and excitation mechanism, which was used to screen the strong discrimination features of pedestrian. Moreover, it used two public pedestrian datasets, Caltech and INRIA. It added SFCM module and AFCM module one by one in the benchmark framework, which verified the validity of the designed modules. Compared with some existing person detection algorithms, the experimental results show that the proposed method has better detection performance and miss rate dropped to 9.13% and 9.46% respectively.

Foundation Support

国家自然科学基金资助项目(61806033)
重庆市重点产业共性关键技术创新专项(cstc2017zdcy-zdyfX0012)
国家社会科学基金西部项目(18XGL013)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.02.0032
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 7
Section: Technology of Graphic & Image
Pages: 2202-2205,2226
Serial Number: 1001-3695(2020)07-059-2202-04

Publish History

[2020-07-05] Printed Article

Cite This Article

陈乔松, 弓攀豪, 申发海, 等. 基于自适应特征卷积网络的行人检测方法 [J]. 计算机应用研究, 2020, 37 (7): 2202-2205,2226. (Chen Qiaosong, Gong Panhao, Shen Fahai, et al. Pedestrian detection method based on adaptive feature convolution network [J]. Application Research of Computers, 2020, 37 (7): 2202-2205,2226. )

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.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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