A human eye detection algorithm in complex scenarios

被引：0

作者：

Cui J. ^{[1
]}

Cao H. ^{[1
]}

Zhang Y. ^{[1
]}

Luo S. ^{[2
]}

Li J. ^{[2
]}

Wang H. ^{[1
,2
]}

机构：

[1] School of Information Science and Technology, North China University of Technology, Beijing

[2] School of Software, Beihang University, Beijing

来源：

Beijing Hangkong Hangtian Daxue Xuebao/Journal of Beijing University of Aeronautics and Astronautics | 2021年 / 47卷 / 01期

关键词：

Complex scenarios; Deep learning; Human eye detection; Multi-scale features; Small target detection;

D O I：

10.13700/j.bh.1001-5965.2019.0641

中图分类号：

学科分类号：

摘要：

Aiming at the problem of human eye detection in complex scenes, indirect methods and direct methods have certain limitations. A direct human eye detection method which is independent of face detection is proposed. The proposed method detects eyes under multiple scales especially small scale in complex scenarios. The improvement of the proposed method consists of improving small-scale human eye detection ability by reducing the down-sampling factor and adding extended residual units; ensuring the accuracy of multi-scale human eye detection by concatenating the multi-scale features; improving human eye detection efficiency by reducing the number of feature output channels to simplify the complexity of the model. The experimental results show that the proposed model can distinguish the left and right eyes effectively under small scale and has good performance with infrared data. The training and test on DIF dataset show that the human eye detection precision of the proposed method is 82.59%, and the detection rate is 30.5 fps. © 2021, Editorial Board of JBUAA. All right reserved.

引用

页码：38 / 44

页数：6

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