Periodic Variance Maximization Using Generalized Eigenvalue Decomposition Applied to Remote Photoplethysmography Estimation
Abstract
A generic periodic variance maximization algorithm to extract periodic or quasi-periodic signals of unknown periods embedded into multi-channel temporal signal recordings is described in this paper. The algorithm combines the notion of maximizing a periodicity metric combined with the global optimization scheme to estimate the source periodic signal of an unknown period. The periodicity maximization is performed using Generalized Eigenvalue Decomposition (GEVD) and the global optimization is performed using tabu search. A case study of remote photoplethysmography signal estimation has been utilized to assess the performance of the method using videos from public databases UBFC-RPPG [1] and MMSE-HR [31]. The results confirm the improved performance over existing state of the art methods and the feasibility of the use of the method in a live scenario owing to its small execution time.
Cite
Text
Macwan et al. "Periodic Variance Maximization Using Generalized Eigenvalue Decomposition Applied to Remote Photoplethysmography Estimation." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2018. doi:10.1109/CVPRW.2018.00181Markdown
[Macwan et al. "Periodic Variance Maximization Using Generalized Eigenvalue Decomposition Applied to Remote Photoplethysmography Estimation." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2018.](https://mlanthology.org/cvprw/2018/macwan2018cvprw-periodic/) doi:10.1109/CVPRW.2018.00181BibTeX
@inproceedings{macwan2018cvprw-periodic,
title = {{Periodic Variance Maximization Using Generalized Eigenvalue Decomposition Applied to Remote Photoplethysmography Estimation}},
author = {Macwan, Richard and Bobbia, Serge and Benezeth, Yannick and Dubois, Julien and Mansouri, Alamin},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
year = {2018},
pages = {1332-1340},
doi = {10.1109/CVPRW.2018.00181},
url = {https://mlanthology.org/cvprw/2018/macwan2018cvprw-periodic/}
}