Non-contact heart rate measurement has been widely utilized in multiple applications. The Eulerian Video Magnification algorithm proposed by MIT CSAIL group in 2012 can be used to magnify the subtle color variation and small motion in videos and can be used to extract cardio-features through photoplethysmography method. In this study, we intend to improve the accuracy of heart rate prediction for the Eulerian Video Magnification method. With the selected region of interest and the peak detection algorithm, we found out that the signal of the Y component in YIQ color spectrum is more consistent than that of the I component in terms of heart rate estimation. The result also demonstrated that the heart rate extracted under 30 frames per second (fps) was more accurate than which extracted under 60 fps. With an illumination level higher than 1500 lx and a frame rate of 30 fps, the error of heart rate extraction compared to oximeter measurement was 5% while using GoPro Hero 6 for recording. Further data processing and false peak detection are necessary for accurate heart rate variability characterization.