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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 2
593-597

Real-time small object detection method based on improved PVANet

Duan Binghuan
Wen Pengcheng
Li Peng
Aviation Key Laboratory of Science & Technology on Airborne & Missile-borne Computer, AVIC Xi'an Aeronautical Computing Technique Research Institute, Xi'an 710065, China
DOI: 10.19734/j.issn.1001-3695.2018.06.0577

Abstract

Existing object detection algorithms are mainly aimed at detecting big objects in an image. Research on small object detection is still too scarce and there are problems with low detection accuracy and failure to meet the real-time requirement. This paper proposed a real-time small object detection method based on deep learning framework PVANet. Firstly, it built a benchmark dataset especially for small object detection problem. The dataset consisted of small objects covering a very small part of an image and also contained some interferences such as truncation and overlap. Secondly, combining with the region proposal network(RPN), it designed a strategy to generate high-quality candidate proposals for small objects to raise the detection accuracy and speed. Finally, it adopted two new learning rate policies "step and inv" to further enhance the detection accuracy. The proposed method achieved the mAP(mean average precision) by 10.67% and speed by 30% improvement over the original PVANet algorithm. Experimental results show that this method is effective on small object detection and can run in real-time.

Foundation Support

航空科学基金资助项目(2015ZC31005,2017ZC31008)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.06.0577
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 2
Section: Technology of Graphic & Image
Pages: 593-597
Serial Number: 1001-3695(2020)02-061-0593-05

Publish History

[2020-02-05] Printed Article

Cite This Article

段秉环, 文鹏程, 李鹏. 基于改进PVANet的实时小目标检测方法 [J]. 计算机应用研究, 2020, 37 (2): 593-597. (Duan Binghuan, Wen Pengcheng, Li Peng. Real-time small object detection method based on improved PVANet [J]. Application Research of Computers, 2020, 37 (2): 593-597. )

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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