Biometrics, an integral component of Identity Science, is widely used in several large-scale-
county-wide projects to provide a meaningful way of recognizing individuals. Among existing …

This paper is based on a disruptive hypothesis for periocular biometrics-in visible-light data,
the recognition performance is optimized when the components inside the ocular globe (the …

Periocular refers to the facial region in the vicinity of the eye, including eyelids, lashes and
eyebrows. While face and irises have been extensively studied, the periocular region has …

Augmented and virtual reality deployment is finding increasing use in novel applications.
Some of these emerging and foreseen applications allow the users to access sensitive …

Open-source software development kits are vital to (iris) biometric research in order to
achieve comparability and reproducibility of research results. In addition, for further …

Periocular is one of the promising biometric traits for human recognition. It encompasses a
surrounding area of eyes that includes eyebrows, eyelids, eyelashes, eye-folds, eyebrows …

Deep-learning based periocular recognition systems typically use overparameterized deep
neural networks associated with high computational costs and memory requirements. This is …

This paper presents recent advances in biometric recognition, where we focus on face,
fingerprint and iris recognition, which are major research topics on biometric recognition. We …

Current periocular and face recognition approaches utilize computationally costly deep
neural networks, achieving notable recognition accuracies. Deploying such solutions in …

This work addresses the challenge of building an accurate and generalizable periocular
recognition model with a small number of learnable parameters. Deeper (larger) models are …