Abstract
Physiological signals provide a reliable method to identify the physical and mental state of a person at any given point in time. Accordingly, there is a myriad of techniques used to extract physiological signals from the human body. However, these techniques often require direct contact with the body. This demands the cooperation of the individual as well as the human effort required to connect devices and collect measurements.In this paper, we propose reliable, non-contact based methods for extracting respiration rate and heart rate from thermal images using a large dataset of human thermal recordings. These methods leverage a combination of image and signal processing techniques in order to extract and filter physiological signals from the thermal domain. Our results evidently show that features extracted from thermal images highly correlate with the ground truth measurements as well as indicate the feasibility of developing non-contact based methods to extract physiological signals.