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.
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Acknowledgement
This work was funded in part by a gift from EyeVerify, Inc. (dba ZOLOZ) an affiliate of Ant Group Co., Ltd., and its affiliates. Dr. Derakhshani is also a consultant for ZOLOZ.
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Nguyen, H.(., Reddy, N., Rattani, A., Derakhshani, R. (2021). VISOB 2.0 - The Second International Competition on Mobile Ocular Biometric Recognition. In: Del Bimbo, A., et al. Pattern Recognition. ICPR International Workshops and Challenges. ICPR 2021. Lecture Notes in Computer Science(), vol 12668. Springer, Cham. https://doi.org/10.1007/978-3-030-68793-9_14
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