  Vital signs, such as heart rate (HR), heart rate variability (HRV),
respiratory rate (RR), are important indicators for a person's health. Vital
signs are traditionally measured with contact sensors, and may be inconvenient
and cause discomfort during continuous monitoring. Commercial cameras are
promising contact-free sensors, and remote photoplethysmography (rPPG) have
been studied to remotely monitor heart rate from face videos. For remote RR
measurement, most prior art was based on small periodical motions of chest
regions caused by breathing cycles, which are vulnerable to subjects' voluntary
movements. This paper explores remote RR measurement based on rPPG obtained
from face videos. The paper employs motion compensation, two-phase temporal
filtering, and signal pruning to capture signals with high quality. The
experimental results demonstrate that the proposed framework can obtain
accurate RR results and can provide HR, HRV and RR measurement synergistically
in one framework.
