This paper investigates non-invasive, non-contact techniques for detecting heart rate variations from facial videos. A comprehensive analysis and comparison of two algorithms for non-invasive, non-contact heart rate detection are presented. Both algorithms begin by selecting a region of interest and extracting remote photoplethysmography signals from color variation. However, one of the algorithms applies additional steps such as non-rigid motion elimination to further improve the quality of signal. While remote heart rate detection algorithms are improving, they remain impractical for real-world applications due to high error rates and lack of reliability. This research advances development of sophisticated heart rate monitoring and analysis tools for the future, paving the way for innovations in cardiovascular health technology.