A low-cost and calibration-free gaze estimator for soft biometrics: an explorative study

Abstract Soft biometric systems have spread among recent years, both for powering classical biometrics, as well as stand alone solutions with several application scopes ranging from digital signage to human-robot interaction. Among all, in the recent years emerged the possibility to consider as a soft biometrics also the temporal evolution of the human gaze and some recent works in the literature explored this exciting research line by using expensive and (perhaps) unsafe devices which require user cooperation to be calibrated. This work is instead the first attempt to perform biometric identification of individuals on the basis of data acquired by a low-cost, non-invasive, safe and calibration-free gaze estimation framework consisting of two main components conveniently combined and performing user's head pose estimation and eyes' pupil localization on data acquired by a RGB-D device. The experimental evidence of the feasibility of using the proposed framework as soft-biometrics is given on a set of users watching three benchmark heterogeneous videos in an unconstrained environment.