Abstract
Video-based remote heart rate detection is a promising technology that can offer convenient and low-cost heart rate monitoring within, but not limited to, the clinical environment, especially when attaching electrodes or pulse oximeters on a person is not possible or convenient. In this work, we examined common steps used in video-based remote heart rate detection algorithms, in order to evaluate their effect on the overall performance of the remote heart rate detection pipeline. Various parameters of the examined methods were evaluated on three public and one proprietary dataset in order to establish a video-based remote heart rate detection pipeline that provides the most balanced performance across various diverse datasets. The experimental evaluation demonstrated the effect and contribution of each step and parameter set on the estimation of the heart rate, resulting in an optimal configuration that achieved a best RMSE value of 9.51.
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