Abstract—Some experiments on a face verification tool based on
FaceNet are presented in this paper. The task of the system
is to perform face verification in a real-time assistive system
aiming at facilitating the approach between a blind person and
a preselected acquaintance of his/her who enters the field of view.
Face detection is made easier by the fact that an almost frontal
view of the face is highly probable; verification on the contrary
is difficult due to the poor quality of the acquired images and to
the necessity of achieving a very low error rate.
A custom database consisting of subjects required for verification
is populated with face images provided by a suitable detection
tool. The cascade of FaceNet and a Bayesian Classifier proves to
be an effective tool for this unconstrained face verification task.
