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Comparison of region of interest segmentation methods for video-based heart rate measurements

Abstract : 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.
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Contributor : Yannick Benezeth Connect in order to contact the contributor
Submitted on : Thursday, November 29, 2018 - 11:19:29 AM
Last modification on : Friday, August 5, 2022 - 2:54:00 PM


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  • HAL Id : hal-01939138, version 1


Peixi Li, Yannick Benezeth, Keisuke Nakamura, Randy Gomez, Chao Li, et al.. Comparison of region of interest segmentation methods for video-based heart rate measurements. IEEE International Conference on Bioinformatics and Bioengineering, Oct 2018, Taichung, Taiwan. ⟨hal-01939138⟩



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