activity
20202023
most citedIris Recognition Performance in Children: A Longitudinal Study

14 citations · 23 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2023

Uniqueness of Iris Pattern Based on AR Model

Katelyn M. Hampel, Jinyu Zuo, Priyanka Das +4

The assessment of iris uniqueness plays a crucial role in analyzing the capabilities and limitations of iris recognition systems. Among the various methodologies proposed, Daugman'…

cs.CV2023★ 9 cited

Empirical Assessment of End-to-End Iris Recognition System Capacity

Priyanka Das, Richard Plesh, Veeru Talreja +4

Iris is an established modality in biometric recognition applications including consumer electronics, e-commerce, border security, forensics, and de-duplication of identity at a na…

cs.CV2023

Longitudinal Performance of Iris Recognition in Children: Time Intervals up to Six years

Priyanka Das, Naveen G Venkataswamy, Laura Holsopple +3

The temporal stability of iris recognition performance is core to its success as a biometric modality. With the expanding horizon of applications for children, gaps in the knowledg…

eess.IV2021★ 14 cited

Iris Recognition Performance in Children: A Longitudinal Study

Priyanka Das, Laura Holsopple, Dan Rissacher +2

There is uncertainty around the effect of aging of children on biometric characteristics impacting applications relying on biometric recognition, particularly as the time between e…

eess.IV2020

Analysis of Dilation in Children and its Impact on Iris Recognition

Priyanka Das, Laura Holsopple, Michael Schuckers +1

The dilation of the pupil and it's variation between a mated pair of irides has been found to be an important factor in the performance of iris recognition systems. Studies on adul…

cs.CV2020

Iris Liveness Detection Competition (LivDet-Iris) -- The 2020 Edition

Priyanka Das, Joseph McGrath, Zhaoyuan Fang +20

Launched in 2013, LivDet-Iris is an international competition series open to academia and industry with the aim to assess and report advances in iris Presentation Attack Detection…