Abstract
Estimating heart rate (HR) accurately using face videos acquired from a low cost camera in contactless manner is of paramount importance for many real-world applications. Such existing systems perform spuriously due to change in camera parameters, respiration, facial expressions and environmental factors. This paper mitigates the issues for accurate HR estimation. The face video consisting of frontal, profile or multiple faces is divided into multiple overlapping fragments to determine HR estimates. The HR estimates are fused using quality-based fusion which aims to minimize illumination and face deformations. Experimental results demonstrate that the proposed system exhibit better performance than the state of the art systems and establishes the efficacy of the quality-based fusion in HR estimation.
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