Remote heart rate estimation based on convolutional neural network and regional adaptive weighting

Shuoyang Feng, Jianing Kang, Xiaoyi Feng, Lei Tang, Zhaoqiang Xia

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

In this paper, a heart rate prediction algorithm based on onedimensional convolutional neural network and adaptive selection of multi-region of interest signals is proposed. Firstly, different from choosing fixed region of interest (ROI) for extracting heart beat signal and facial movements, this article selects the multiple ROIs and extracts the characteristics of Chrominance signals based on the spectrum similarity to assess the significance of heart rate signals. Then signal integration is employed to effectively improve the signal-to-noise ratio of the input signal. Secondly, the existing heart rate detection methods based on convolutional neural network mostly adopt two-dimensional, three-dimensional and other large-scale networks, with large number of parameters and slow operation speed. In this paper, a light weight one-dimensional convolutional neural network is proposed. The network takes onedimensional heart rate detected signals extracted from video as input, which not only ensures the integrity of heart rate signals but also reduces the number of network parameters. Experiments on MAHNOB-HCI database show that the proposed algorithm has achieved better performance.

源语言英语
主期刊名ICBBT 2021 - Proceedings of 2021 13th International Conference on Bioinformatics and Biomedical Technology
出版商Association for Computing Machinery
217-223
页数7
ISBN(电子版)9781450389655
DOI
出版状态已出版 - 21 5月 2021
活动13th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2021 - Xi'an, 中国
期限: 21 5月 202123 5月 2021

出版系列

姓名ACM International Conference Proceeding Series

会议

会议13th International Conference on Bioinformatics and Biomedical Technology, ICBBT 2021
国家/地区中国
Xi'an
时期21/05/2123/05/21

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