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基于近红外图像的嵌入式人员在岗检测系统

Embedded Personnel On-the-job Detection System Based on Near-infrared Image

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摘要

在岗检测是现代安防领域中视频分析的一个重要研究方向,应用领域非常广泛。本文设计并实现了一种嵌入式人员在岗检测系统,为了提高此嵌入式系统的运行速度,提出了改进的人脸特征点检测方法;并且为了提高系统的检测准确率,建立了一个近红外人脸样本库。该系统通过近红外摄像头采集实时图像,然后进行人脸特征点检测,获取被检测人的面部信息。根据违规行为判断准则,判断当前是否出现违规动作并且发出警报。实验结果表明:在规定条件下,系统的人脸特征点检测准确率达到了 95%,针对两种异常情况的检测准确率也都超过了 94%,具有良好的实时性能。

Abstract

On-the-job detection is an important research direction for video analytics in the field of modern security, with a wide range of applications. This study designs and implements an embedded personnel on-the-job detection system. To improve the running speed of this embedded system, we proposed an improved face landmarks detection method, and to improve the accuracy of detection by the system, we established a near-infrared face database. This system initially collects real-time images through a near-infrared camera; subsequently, it performs face landmark detection to obtain the facial information of the detected person. According to predefined rules to identify violations, the system decides whether an illegal action has occurred and sends out alarm. The experimental results show that the accuracy of face landmark detection by the system reached 95% under the specified conditions, and the detection accuracy rate for two abnormal conditions exceeded 94%, both while maintaining a good real-time performance.

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中图分类号:TP391

所属栏目:红外应用

基金项目:国家自然科学基金(61572356)

收稿日期:2018-07-20

修改稿日期:2018-10-25

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作者单位    点击查看

苏育挺:天津大学电气自动化与信息工程学院,天津 300072
陈 耀:天津大学电气自动化与信息工程学院,天津 300072
吕 卫:天津大学电气自动化与信息工程学院,天津 300072

联系人作者:苏育挺(jxcy@tju.edu.cn)

备注:苏育挺(1972-),男,博士,教授,主要从事数字视频编码,数字视频处理,信息隐藏与数字水印,多媒体信息被动取证等方面的研究。

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引用该论文

SU Yuting,CHEN Yao,LYU Wei. Embedded Personnel On-the-job Detection System Based on Near-infrared Image[J]. Infrared Technology, 2019, 41(4): 377-382

苏育挺,陈 耀,吕 卫. 基于近红外图像的嵌入式人员在岗检测系统[J]. 红外技术, 2019, 41(4): 377-382

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