DEEP PERSON IDENTIFICATION USING SPATIOTEMPORAL FACIAL MOTION AMPLIFICATION

We explore the capabilities of a new biometric trait, which is based on information extracted through facial motion amplification. Unlike traditional facial biometric traits, the new biometric does not require the visibility of facial features that are critical in common facial biometric algorithms. The proposed biometric can be formed by recording the face of a subject for a few seconds using an ordinary camera. Here, a novel 3D facial blood flow map is constructed using small motion amplification. Experiments show that the proposed approach provides significant discriminatory capacity over different training and testing days and can be potentially used as a complementary trait to traditional facial biometrics.