Spoofing attempt detection using gaze colocation

Spoofing attacks on biometric systems are one of the major impediments to their use for secure unattended applications. This paper presents a novel method for face liveness detection by tracking the gaze of the user with an ordinary webcam. In the proposed system, an object appears randomly on the display screen which the user is required to look at while their gaze is measured. The visual stimulus appears in such a way that it repeatedly directs the gaze of the user to specific points on the screen. Features extracted from images captured at these sets of colocated points are used to estimate the liveness of the user. A scenario is investigated where genuine users track the challenge with head/eye movements whereas the impostors hold a photograph of the target user and attempt to follow the stimulus during simulated spoofing attacks. The results from the experiments indicate the effectiveness of the gaze colocation feature in detecting spoofing attack.