pyVHR: a Python framework for remote photoplethysmography

Remote photoplethysmography (rPPG) aspires to automatically estimate heart rate (HR) variability from videos in realistic environments. A number of effective methods relying on data-driven, model-based and statistical approaches have emerged in the past two decades. They exhibit increasing ability t...

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Veröffentlicht in:	PeerJ. Computer science Jg. 8; S. e929
Hauptverfasser:	Boccignone, Giuseppe, Conte, Donatello, Cuculo, Vittorio, D’Amelio, Alessandro, Grossi, Giuliano, Lanzarotti, Raffaella, Mortara, Edoardo
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States PeerJ, Inc 15.04.2022 PeerJ PeerJ Inc
Schlagworte:	Blood volume Case studies Cognitive science Computer Science Computer Vision Computer Vision and Pattern Recognition Contactless monitoring Datasets Deep rPPG Deepfake Detection Heart rate Heart Rate Estimation Human-Computer Interaction Image Processing Learning Pipelining (computers) Python Remote photoplethysmography Signal and Image Processing Signal processing Statistical analysis Video Deepfake Detection Remote photoplethysmography Contactless monitoring Deep rPPG Heart Rate Estimation Computer Vision Remote photoplethysmography Subjects Human-Computer Interaction
ISSN:	2376-5992, 2376-5992
Online-Zugang:	Volltext
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