Analysis of Non-invasive Video Based Heart Rate Monitoring System obtained from Various Distances and Different Facial Spot

Heart rate (HR) is one of the crucial indicators for human psychological. In recent works, it has been shown that a standard camera is able to detect illumination changes in the face skin due to the human cardiac pulse and this can be used to estimate the human HR. However most of previous systems work on near distance mode with a single face patch, thus the expediency of the camera based remote heart rate estimation for long range distances remains ambiguous. This paper has proposed a solution by analyzing an optimal framework that able to works properly under the mentioned issues. Initially, presumable facial landmarks are estimated by applying cascaded of regression mechanism. Then, the region of interest (ROI) was selected based on the facial landmarks in the location where non rigid motion is minimal. Temporal photoplethysmograph (PPG) signal is extracted from the ROI and the unwanted signal such as environment illumination signal or motion artifact signal is eliminated by using Independent Component Analysis (ICA) filter. Then, PPG signal is further processed using series of temporal filter to exclude frequencies outside the range of interest prior to estimate the HR. Since, the HR is estimated independently from multiple local regions, a histogram analysis is constructed to calculate the average HR estimation accurately. From the experiments, it can be concluded that the HR can be detected up to 5 meters range with 94% accuracy using full face region.