A Comparison of Bounding Box and Landmark Detection Methods for Video-Based Heart Rate Estimation
This is an incremental improvement for remote health monitoring applications.
The paper tackled the problem of estimating heart rate from video using remote photoplethysmography by comparing bounding box and landmark detection methods, finding that the landmark-based approach reduced result variance with a standard deviation over 4 times smaller (4.171 vs. 18.720).
Remote Photoplethysmography (rPPG) uses the cyclic variation of skin tone on a person's forehead region to estimate that person's heart rate. This paper compares two methods: a bounding box-based method and a landmark-detection-based method to estimate heart rate, and discovered that the landmark-based approach has a smaller variance in terms of model results with a standard deviation that is more than 4 times smaller (4.171 compared to 18.720).