Hoffman, Wouter; Lakens, Daniel (2020): Public Benchmark Dataset for Testing rPPG Algorithm Performance. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/uuid:2ac74fbd-2276-44ad-aff1-2f68972b7b51

Dataset

• Artificial Intelligence and Image Processing
• Information Systems

PPGi, Public benchmarking, Remote photoplethysmography (rPPG), Reproducibility

4TU General Terms of Use

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Wouter Hoffman , Daniel Lakens

The current needs in remote photoplethysmography (rPPG) research were investigated and it was concluded there is a lack of reproducibility and comparability in the current rPPG research. Three main challenges for rPPG algorithms were defined and incorporated in the dataset; lighting & skin tone, motion robustness and high heart rates & pulse-rate change robustness. Videos accompanied by ECG measurements were recorded to create test material for these challenges.

• 2020-07-22 first online, published, posted

4TU.Centre for Research Data

media types: application/zip, text/plain, video/avchd, video/x-msvideo

• https://osf.io/xjf7u/

• TU/e

TU Eindhoven, Department of Industrial Engineering & Innovation Sciences