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Fusing Iris and Periocular Region for User Verification in Head Mounted Displays

: Boutros, Fadi; Damer, Naser; Raja, Kiran; Ramachandra, Raghavendra; Kirchbuchner, Florian; Kuijper, Arjan


International Society of Information Fusion -ISIF-:
FUSION 2020, 23rd International Conference on Information Fusion
Piscataway, NJ: IEEE, 2020
ISBN: 978-0-578-64709-8
ISBN: 978-1-7281-6830-2
8 S.
International Conference on Information Fusion (FUSION) <23, 2020, Online>
Bundesministerium für Bildung und Forschung BMBF (Deutschland)
Fraunhofer IGD ()
Lead Topic- Smart City; Lead Topic- Visual Computing as a Service; Research Line- Computer vision (CV); Research Line- Human computer interaction (HCI); Biometrics; Information fusion; Deep learning; Head mounted displays; Iris recognition; ATHENE; CRISP

The growing popularity of Virtual Reality and Augmented Reality (VR/AR) devices in many applications also demands authentication of users. As the devices inherently capture the eye image while capturing the user interaction, the authentication can be devised using the iris and periocular recognition. While both iris and periocular data being non-ideal unlike the data captured from standard biometric sensors, the authentication performance is expected to be lower. In this work, we present and evaluate a fusion framework for improving the biometric authentication performance. Specifically, we employ score-level fusion for two independent biometric systems of iris and periocular region to avoid expensive feature-level fusion. With a detailed evaluation of three different score-level fusion after the score normalization on a dataset of 12579 images, we report the performance gain in authentication using score-level fusion for iris and periocular recognition.