Analysis of Factors on BVP Signal Extraction Based on Imaging Principle

Xiaobiao Zhang, Xiaoyi Feng, Zhaoqiang Xia
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引用次数: 3

Abstract

The extraction of human physiological based on face video has become a hot research direction, but few researchers pay attention to the process of signal extraction from an optical perspective. This paper establishes an optical model for human skin, and analyzes the principle of extracting human physiological signals from face video by imaging. Based on this model, the effects of melanin and hemoglobin on BVP (blood volume pulse) signal extraction were analyzed. In addition, this paper introduces the model of camera imaging, and discusses the cause of noise generation, analysis of the impact of two kinds of noise on video quality. Finally, this paper uses the MAHNOB database to carry out the heart rate extraction experiment from video, the experiment concluded that: (1) The face with lighter skin color is more conducive to human heart rate extraction; (2) Reducing the signal-noise ratio through compressing the video quality, the impact on the heart rate estimation error reaches minimum as the signal-noise ratio is 30dB; (3) By compressing the original video resolution, color information in the video is reduced, which has a impact on BVP signals extraction, the information recovery can be performed by the method of super-resolution reconstruction.
基于成像原理的BVP信号提取影响因素分析
基于人脸视频的人体生理特征提取已成为一个热门的研究方向,但很少有研究者从光学角度对信号提取过程进行关注。本文建立了人体皮肤的光学模型,分析了利用成像技术从人脸视频中提取人体生理信号的原理。基于该模型,分析了黑色素和血红蛋白对血容量脉冲信号提取的影响。此外,本文还介绍了摄像机成像的模型,并讨论了噪声产生的原因,分析了两种噪声对视频质量的影响。最后,本文利用MAHNOB数据库对视频进行心率提取实验,实验得出结论:(1)肤色较浅的人脸更有利于人体心率提取;(2)通过压缩视频质量降低信噪比,当信噪比为30dB时,对心率估计误差的影响最小;(3)通过压缩原始视频分辨率,减少了视频中的颜色信息,这对BVP信号的提取有影响,可以通过超分辨率重建的方法进行信息恢复。
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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