Automatic RoI Detection for Camera-Based Pulse-Rate Measurement

Abstract

AbstractRemote photoplethysmography (rPPG) enables contactless measurement of pulse-rate by detecting pulse-induced colour changes on human skin using a regular camera. Most of existing rPPG methods exploit the subject face as the Region of Interest (RoI) for pulse-rate measurement by automatic face detection. However, face detection is a suboptimal solution since (1) not all the subregions in a face contain the skin pixels where pulse-signal can be extracted, (2) it fails to locate the RoI in cases when the frontal face is invisible (e.g., side-view faces). In this paper, we present a novel automatic RoI detection method for camera-based pulse-rate measurement, which consists of three main steps: subregion tracking, feature extraction, and clustering of skin regions. To evaluate the robustness of the proposed method, 36 video recordings are made of 6 subjects with different skin-types performing 6 types of head motion. Experimental results show that for the video sequences containing subjects with brighter skin-types and modest body motions, the accuracy of the pulse-rates measured by our method (\(94\,\%\)) is comparable to that obtained by a face detector (\(92\,\%\)), while the average SNR is significantly improved from 5.8 dB to 8.6 dB.KeywordsSkin RegionSkin PixelFeature CornerSkin SegmentationAutomatic Face DetectionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.