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基于改进DRSN的人脸视频心率检测方法研究

赵娅 吕浩原 田晓彩 陆谣

计算机与数字工程2025,Vol.53Issue(11):3155-3161,7.
计算机与数字工程2025,Vol.53Issue(11):3155-3161,7.DOI:10.3969/j.issn.1672-9722.2025.11.029

基于改进DRSN的人脸视频心率检测方法研究

Research on Heart Rate Detection Method of Face Video Based on Improved DRSN

赵娅 1吕浩原 1田晓彩 2陆谣1

作者信息

  • 1. 东北石油大学计算机与信息技术学院 大庆 163318
  • 2. 湖南省人民医院 长沙 410000
  • 折叠

摘要

Abstract

At present,the non-contact heart rate detection method based on face video has many problems,such as large noise interference,low accuracy and poor robustness.This paper proposes a heart rate detection method for face video based on im-proved DRSN,which can effectively solve the above problems.The improved DRSN network,on the one hand,modifies SENet in the original DRSN network to ECA-Net to effectively avoid the impact of SENet dimensionality reduction on the attention of learning channels,while maintaining the information sharing between channels,so that the channel attention mechanism can better serve the soft threshold function.On the other hand,it replaces the ReLU activation function in the original DRSN network with Leaky ReLU to reduce the occurrence of dead neurons caused by the ReLU activation function.The experimental results show that the MAE de-creases by 18.7%,RMSE decreases by 17.6%,SD decreases by 17.9%,and Pearson correlation coefficient r increases by 4.3%on the VIPL dataset.In PURE data set,MAE decreases by 9.5%,RMSE decreases by 15.2%,SD decreased by 10%,and Pearson cor-relation coefficient r increases by 0.3%.It has been verified that the improved face video heart rate detection method has higher de-tection accuracy and stronger anti-interference ability,effectively improving the accuracy and robustness of face video heart rate de-tection.

关键词

DRSN/人脸视频/心率检测/ECA-Net/Leaky ReLU

Key words

DRSN/face video/heart rate detection/ECA-Net/Leaky ReLU

分类

信息技术与安全科学

引用本文复制引用

赵娅,吕浩原,田晓彩,陆谣..基于改进DRSN的人脸视频心率检测方法研究[J].计算机与数字工程,2025,53(11):3155-3161,7.

基金项目

黑龙江省自然科学基金项目(编号:LH2022F006) (编号:LH2022F006)

湖南省卫生健康委科研课题(编号:202103101352)资助. (编号:202103101352)

计算机与数字工程

1672-9722

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