A robust real time system for remote heart rate measurement via camera

Heart rate (HR) is an important indicator of human health status. Traditional heart rate measurement methods rely on contact-based sensors or electrodes, which are inconvenient and troublesome for users. Remote sensing of the photoplephysmography (PPG) signal using a video camera provides a promising means to monitor vital signs of people without the need of any physical contact. However, until recently, most of the literature papers approaching this problem have only reported results from off-line recording videos taken under well controlled environments. In this paper, we propose a method to improve HR measurement accuracy under challenging environments involving factors such as subjects movement, complicated facial models (i.e., hair, glass, beards, etc.), subjects' distance to camera, and low illumination condition. We also build a framework for real-time measuring system and construct a stable model for recording and displaying results for long term heart rate monitoring. We tested our system on challenging dataset, and demonstrated that our method not only deals with real-time, on-line measurement tasks, but also outperforms others' works.