Biometric Identification and Presentation-Attack Detection using Micro- and Macro-Movements of the Eyes

Abstract

We study involuntary micro-movements of both eyes, in addition to saccadic macro-movements, as biometric characteristic. We develop a deep convolutional neural network that processes binocular oculomotoric signals and identifies the viewer. In order to be able to detect presentation attacks, we develop a model in which the movements are a response to a controlled stimulus. The model detects replay attacks by processing both the controlled but randomized stimulus and the ocular response to this stimulus. We acquire eye movement data from 150 participants, with 4 sessions per participant. We observe that the model detects replay attacks reliably; compared to prior work, the model attains substantially lower error rates.