6533b82cfe1ef96bd12901ad
RESEARCH PRODUCT
Comparison of region of interest segmentation methods for video-based heart rate measurements
Yannick BenezethKeisuke NakamuraRandy GomezChao LiFan YangPeixi Lisubject
Heart Rate (HR)Computer science[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing0206 medical engineering02 engineering and technology01 natural sciencesSignal[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingRegion of interestPhotoplethysmogramSegmentationComputer visionVideo basedPixelbusiness.industryremote photoplethysmography (rPPG)010401 analytical chemistryPerspective (graphical)[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Region of Interest (ROI)020601 biomedical engineering0104 chemical sciencesRGB color modelArtificial intelligencebusinessdescription
International audience; Conventional contact photoplethysmography (PPG) sensors are not suitable in situations of skin damage or when unconstrained movement is required. As a consequence, remote photoplethysmography (rPPG) has recently emerged because it provides remote physiological measurements without expensive hardware and improves comfort for long-term monitoring. RPPG estimation methods use the spatially averaged RGB values of pixels in a Region Of Interest (ROI) to generate a temporal RGB signal. The selection of ROI is a critical first step to obtain reliable pulse signals and must contain as many skin pixels as possible with a low percentage of non-skin pixels. In this paper, we experimentally compare seven ROI segmentation methods in the perspective of heart rate (HR) measurements with dedicated metrics. The algorithms are compared using our in-house database UBFC-RPPG, comprising of 53 videos specifically geared towards rPPG analysis.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2018-10-01 |