基于视频的实时心率检测，用于驾驶舱内的智能手机

2022 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS) Pub Date : 2022-11-24 DOI:10.1109/IoTaIS56727.2022.9975941

Walaa Othman, A. Kashevnik

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引用次数: 3

摘要

利用物联网技术开发车辆，包括驾驶员健康监测系统、驾驶员安全系统和事故预防系统，在过去几年引起了研究人员的关注。监控系统应防止任何危险情况，并使驾驶员在车内感到舒适。本文介绍了一种基于智能手机摄像头的远程视频实时心率检测方法，该方法可用于分析驾驶员的生理参数，以提高驾驶安全性。我们建议使用3DDFA进行自动面部地标检测来提取驾驶员的面部，并使用基于3d分类的模型来检测心率。实验结果表明，LGI-PPGI数据集的平均绝对误差(MAE)为6.8，我们的DriverMVT数据集的平均绝对误差为18.68。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Video-Based Real-Time Heart Rate Detection for Drivers Inside the Cabin Using a Smartphone

Developing vehicles with the Internet of Thing technology including driver health monitoring systems, driver safety systems, and accident prevention has drawn the attention of researchers in the last few years. The monitoring system should prevent any dangerous situation and be comfortable for the driver inside the cabin. In this paper, we introduce a remote video-based method for detecting the heart rate in real-time using smartphone cameras, which can be used for the analysis of the driver’s physiological parameters to enhance driving safety. We propose to use 3DDFA for automatic facial landmarks detection to extract the driver’s face and a 3d-classification-based model for detecting the heart rate. The experiments showed good results with mean absolute error (MAE) equal to 6.8 on the LGI-PPGI dataset and 18.68 on our DriverMVT dataset that was recorded in the wild.

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2022 IEEE International Conference on Internet of Things and Intelligence Systems (IoTaIS)

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