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LCOMS Lab's approach to the Vision For Vitals (V4V) Challenge

Abstract : We present in this paper the LCOMS Lab's approach to the 1st Vision For Vitals (V4V) Challenge organized within ICCV2021. The V4V challenge was focused on computer vision methods for vitals signs measurement from facial videos, including pulse rate (PR) and respiratory rate. We propose a novel end-to-end architecture based on a deep spatiotemporal network for pulse rate estimation from facial video recordings. Unlike existing methods, we predict the pulse rate value directly without passing by iPPG signal extraction and without incorporating any prior knowledge or additional processing steps. We built our network using 3D Depthwise Separable Convolution layers with residual connections to extract spatial and temporal features simultaneously. This is very suitable for real-time measurement because it requires a reduced number of parameters and a short video fragment. The obtained results seem very satisfactory and promising, especially since the experiments were conducted in challenging dataset collected in uncontrolled conditions.
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Contributor : Frédéric Bousefsaf Connect in order to contact the contributor
Submitted on : Tuesday, October 12, 2021 - 10:36:43 AM
Last modification on : Wednesday, October 13, 2021 - 3:11:18 AM


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  • HAL Id : hal-03374480, version 1



Yassine Ouzar, Djamaleddine Djeldjli, Frédéric Bousefsaf, Choubeila Maaoui. LCOMS Lab's approach to the Vision For Vitals (V4V) Challenge. International Conference on Computer Vision (ICCV) Workshops, Oct 2021, -, France. ⟨hal-03374480⟩



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