Name
Title | ||
|---|---|---|
New insights on super-high resolution for video-based heart rate estimation with a semi-blind source separation method. |
Abstract | ||
|---|---|---|
Remote photoplethysmography (rPPG), a non-contact technique to estimate heart rates (HR) from video recordings, has attracted much attention from researchers in recent years. It is well-known that rPPG signals can be extracted from low-resolution videos. However, the measurement quality may degrade due to camera quantization noise if only a small number of pixels are within the skin region of interest. The purpose of this paper is to comprehensively investigate the benefit of using a super-high resolution for the rPPG-based HR estimation under various shooting distances. A new semi-blind source separation (semi-BSS) rPPG method, which is proposed to combine the advantages of BSS and model-based methods, is fully tested on both the public UBFC-RPPG and self-collected video datasets. The experimental results demonstrate that the new semi-BSS method outperforms several existing techniques. A consistent and remarkable improvement on the rPPG signal quality has been observed with the super-high resolution when the shooting distance is no less than 1.0 m. This indicates that selecting an appropriate resolution based on a given shooting distance also plays a crucial role to improve the quality of rPPG measurements. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.compbiomed.2019.103535 | Computers in Biology and Medicine |
Keywords | DocType | Volume |
00-01,99-00 | Journal | 116 |
ISSN | Citations | PageRank |
0010-4825 | 3 | 0.44 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rencheng Song | 1 | 7 | 1.22 |
| Senle Zhang | 2 | 3 | 0.44 |
| Juan Cheng | 3 | 62 | 11.53 |
| chang li | 4 | 282 | 19.50 |
| Xun Chen | 5 | 458 | 52.73 |