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基于红外注意力提升机制的热成像测温区域实例分割

易诗 李俊杰 贾勇

易诗, 李俊杰, 贾勇. 基于红外注意力提升机制的热成像测温区域实例分割[J]. 电子与信息学报, 2021, 43(12): 3505-3512. doi: 10.11999/JEIT200862
引用本文: 易诗, 李俊杰, 贾勇. 基于红外注意力提升机制的热成像测温区域实例分割[J]. 电子与信息学报, 2021, 43(12): 3505-3512. doi: 10.11999/JEIT200862
Shi YI, Junjie LI, Yong JIA. Instance Segmentation of Thermal Imaging Temperature Measurement Region Based on Infrared Attention Enhancement Mechanism[J]. Journal of Electronics & Information Technology, 2021, 43(12): 3505-3512. doi: 10.11999/JEIT200862
Citation: Shi YI, Junjie LI, Yong JIA. Instance Segmentation of Thermal Imaging Temperature Measurement Region Based on Infrared Attention Enhancement Mechanism[J]. Journal of Electronics & Information Technology, 2021, 43(12): 3505-3512. doi: 10.11999/JEIT200862

基于红外注意力提升机制的热成像测温区域实例分割

doi: 10.11999/JEIT200862
基金项目: 国家自然科学基金(61771096),工业物联网与网络化控制教育部重点实验室开放基金(2020FF06),太赫兹科学技术四川省重点实验室开放基金(THZSC202001)
详细信息
    作者简介:

    易诗:男,1983年生,高级实验师,研究方向为深度学习红外图像处理

    李俊杰:男,1997年生,硕士生,研究方向为深度学习图像处理

    贾勇:男,1986年生,副教授,研究方向为穿墙雷达图像处理

    通讯作者:

    易诗 549745481@qq.com

  • 中图分类号: TN911.73; TP391

Instance Segmentation of Thermal Imaging Temperature Measurement Region Based on Infrared Attention Enhancement Mechanism

Funds: The National Natural Science Foundation of China (61771096), The Key Laboratory of Industrial Internet of Things & Networked Control Foundation, Ministry of Education (2020FF06), The Terahertz Science and Technology Key Laboratory Foundation of Sichuan Province (THZSC202001)
  • 摘要: AI+热成像人体温度监测系统被广泛用于人群密集的人体实时温度测量。此类系统检测人的头部区域进行温度测量,由于各类遮挡,温度测量区域可能太小而无法正确测量。为了解决这个问题,该文提出一种融合红外注意力提升机制的无锚点实例分割网络,用于实时红外热成像温度测量区域实例分割。该文所提出的实例分割网络在检测阶段和分割阶段融合红外空间注意力模块(ISAM),旨在准确分割红外图像中的头部裸露区域,以进行准确实时的温度测量。结合公共热成像面部数据集和采集的红外热成像数据集,制作了“热成像温度测量区域分割数据集”用于网络训练。实验结果表明:该方法对红外热成像图像中头部裸露测温区域的平均检测精度达到88.6%,平均分割精度达到86.5%,平均处理速度达到33.5 fps,在评价指标上优于大多数先进的实例分割方法。
  • 图  1  热成像体温测量方法

    图  2  用于红外热成像温度测量区域分割的无锚点实例分割网络结构

    图  3  红外空间注意力模块结构

    图  4  红外空间注意力模块目标检测阶段有效性测试

    图  5  红外空间注意力模块目标分割阶段有效性测试

    表  1  训练集中各类数据分布

    数据类型带口罩的面部裸露的面部存在各类遮挡的面部
    比例(%)402040
    下载: 导出CSV

    表  2  数据集中标签对应的标注色

    分割类别温度测量区域头发帽子眼镜口罩
    R01390255255
    G1000255105255
    B0139127180210
    下载: 导出CSV

    表  3  ISAM模块目标检测阶段有效性验证实验结果

    结构AP(%)AMP(%)fps
    无注意力提升机制83.780.038.0
    融合CBAM模块85.681.533.5
    融合BAM模块84.881.034.5
    融合ISAM模块88.684.535.5
    下载: 导出CSV

    表  4  ISAM模块目标分割阶段有效性实验结果

    结构AP(%)AMP(%)fps
    无注意力提升机制88.684.535.5
    融合CBAM模块88.684.331.2
    融合BAM模块88.684.132.5
    融合ISAM模块88.686.533.5
    下载: 导出CSV

    表  5  热成像测温区域实例分割方法对比实验结果

    实例分割方法AP(%)AMP(%)fps
    Mask R-CNN83.880.311.5
    YOLACT75.670.138.0
    CenterMask82.878.133.0
    PolarMask83.679.030.5
    本文方法88.686.533.5
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-10-09
  • 修回日期:  2021-04-22
  • 网络出版日期:  2021-07-15
  • 刊出日期:  2021-12-21

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