Periocular Biometrics in Mobile Environment

In this work we study periocular biometrics in a challenging scenario: a mobile environment, where person recognition can take place on a mobile device. The proposed technique, that models session variability, is evaluated for the authentication task on the MOBIO database, previously used in face recognition, and on a novel mobile biometric database named the CPqD Biometric Database, as well as compared to prior work. We show that in this particular mobile environment the periocular region is complementary to face recognition, but not superior, unlike shown in a previous study on a more controlled environment. We show also that a combination with face recognition brings a relative improvement of 5.84% in terms of HTER. Finally, the results of this paper will be reproducible using an open software and a novel Web platform.