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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 3
914-918

Multi-scale and texture feature enhancement for small face detection

Zhang Zhi1
Wang Jin1
Wang Jie1
Zheng Jin2
1. College of Computer Science & Technology, Civil Aviation University of China, Tianjin 300300, China
2. School of Computer Science & Engineering, Beihang University, Beijing 100191, China
DOI: 10.19734/j.issn.1001-3695.2019.12.0696

Abstract

In view of the existing face detection algorithms were difficult to deal with multi-scale, multi-pose face detection, especially for small size face, which encountered the problem of low accuracy, this paper proposed a small size face detection algorithm with multi-scale and texture feature enhanced. In this algorithm, the multi-scale enhancement module could enrich the multi-scale features to improve the detection accuracy of multi-scale face, and the texture feature enhancement module could enhance the high-level semantic information by fusing the low-level texture information, thus, it enhanced the detection ability of small size face. Furthermore, the multi-stage weighted loss functions balanced the output of the network and strengthened the role of each module. The experimental results show that the proposed algorithm can not only achieve real-time computation in detection speed, but also achieve 88.69% accuracy for face detection with less than 60 pixels height in MALF dataset. Compared with the BBFCN algorithm in FDDB dataset, the result is increased by nearly 4%.

Foundation Support

国家自然科学基金资助项目(61876014)
中央高校资助项目(3122019123)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.12.0696
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 3
Section: Technology of Graphic & Image
Pages: 914-918
Serial Number: 1001-3695(2021)03-053-0914-05

Publish History

[2021-03-05] Printed Article

Cite This Article

张智, 王进, 王杰, 等. 多尺度和纹理特征增强的小尺寸人脸检测 [J]. 计算机应用研究, 2021, 38 (3): 914-918. (Zhang Zhi, Wang Jin, Wang Jie, et al. Multi-scale and texture feature enhancement for small face detection [J]. Application Research of Computers, 2021, 38 (3): 914-918. )

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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