Heartbeat Rate Measurement from Facial Video

Abstract

Heartbeat Rate (HR) reveals a person’s health condition. This paper presents an effective system for measuring HR from facial videos acquired in a more realistic environment than the testing environment of current systems. The proposed method utilizes a facial feature point tracking method by combining a‘Good feature to track’ and a ‘Supervised descent method’ in order to overcome the limitations of currently available facial video based HR measuring systems. Such limitations include, e.g., unrealistic restriction of thesubject’s movement and artificial lighting during data capture. A face quality assessment system is also incorporated to automatically discard low quality faces that occur in a realistic video sequence to reduceerroneous results. The proposed method is comprehensively tested on the publicly available MAHNOB-HCI database and our local dataset, which are collected in realistic scenarios. Experimental results show that theproposed system outperforms existing video based systems for HR measurement