  Problem of indirect assessment of heart rate in video is addressed. Several
methods of indirect evaluations (adaptive baselines) were examined on Remote
Physiological Signal Sensing challenge. Particularly, regression models of
dependency of heart rate on estimated age and motion intensity were obtained on
challenge's train set. Accounting both motion and age in regression model led
to top-quarter position in the leaderboard. Practical value of such adaptive
baseline approaches is discussed. Although such approaches are considered as
non-applicable in medicine, they are valuable as baseline for the
photoplethysmography problem.
