  Recently, remote respiratory rate measurement techniques gained much
attention as they were developed to overcome the limitations of device-based
classical methods and manual counting. Many approaches for RR extraction from
the video stream of the visible light camera were proposed, including the pixel
intensity changes method. In this paper, we propose a new method for 1D profile
creation for pixel intensity changes-based method, which significantly
increases the algorithm's performance. Additional accuracy gain is obtained via
a new method of motion signals grouping presented in this work. We introduce
several changes to the standard pipeline, which enables real-time continuous RR
monitoring and allows applications in the human-computer interaction systems.
Evaluation results on two internal and one public datasets showed 0.7 BPM, 0.6
BPM, and 1.4 BPM MAE, respectively.
