no code implementations • 3 Feb 2024 • Jeremy Speth, Nathan Vance, Benjamin Sporrer, Lu Niu, Patrick Flynn, Adam Czajka
We provide thorough experiments demonstrating the suitability of MSPM to support research on rPPG, respiration rate, and PTT.
no code implementations • 16 Mar 2023 • Lu Niu, Jeremy Speth, Nathan Vance, Ben Sporrer, Adam Czajka, Patrick Flynn
In this paper we explored the feasibility of rPPG from non-face body regions such as the arms, legs, and hands.
no code implementations • 11 Mar 2023 • Jeremy Speth, Nathan Vance, Benjamin Sporrer, Lu Niu, Patrick Flynn, Adam Czajka
Extensive experimentation with eight research datasets (rPPG-specific: DDPM, CDDPM, PURE, UBFC, ARPM; deep fakes: DFDC; face presentation attack detection: HKBU-MARs; rPPG outlier: KITTI) show better accuracy of anomaly detection for deep learning models incorporating the proposed training (75. 8%), compared to models trained regularly (73. 7%) and to hand-crafted rPPG methods (52-62%).