Heart rate is one of the most important biological features for health information. Most of the state-of-the-art heart rate monitoring systems relies on invasive technologies that require physical contact with the user. In this paper, we propose a non- invasive technology based on a single camera to measure the users heart rate in real time. The algorithm estimates the heart rate based on facial color changes. The input is a series of video frames with the automatically detected face of the user. A Gaus- sian pyramid spatial filter is applied on the inputs to obtain a down sampled high signal-to-noise ratio images. A temporal Fourier transform is applied to the video to get the signal spec- trum. Next, a temporal band-pass filter is applied on the trans- formed signal in the frequency domain to extract the frequency band of heart beats. The heart rate is then estimated by finding the dominant frequency in the Fourier domain. Further, an in- verse Fourier transform is used on the spectrum to convert the signal back to the time domain. After scaling, the amplified sig- nal is added to the input image to magnify the subtle facial color change that is caused by the heartbeat. We implement on an iPhone 5s using the front facing camera and demonstrate that it has 1.4 bpm error when compared to a standard hearth rate monitor.