VISOB 2.0 - The second international competition on mobile ocular biometric recognition

Abstract

Following the success of VISOB 1.0 visible light ocular biometrics competition at IEEE ICIP 2016, we organized VISOB 2.0 competition at IEEE WCCI 2020. The aim of VISOB 2.0 competition was to evaluate and compare the performance of ocular biometrics recognition approaches in visible light using (a) stacks of five images captured in burst mode and (b) subject-independent evaluation, where subjects do not overlap between training and testing set. We received three submissions in which the authors developed various deep learning based and texture-analysis based methods. The best results were obtained by a team from Federal University of Parana (Curitiba, Brazil), achieving an Equal Error Rate (EER) of 5.25% in a subject-independent evaluation setting.