Publications:Periocular Recognition Using Retinotopic Sampling and Gabor Decomposition
From ISLAB/CAISR
"CAISR research program of the Swedish Knowledge Foundation;EU BBfor2 Marie Curie Initial Training Network "Bayesian Biometrics for Forensics" (FP7- ITN-238803);EU COST Action IC1106 "Integrating Biometrics and Forensics for the Digital Age";Swedish Research Council Postdoctoral Grant "2009-7215";EU FP7 Marie Curie Intra-European Fellowship FP7-PEOPLE-2009-IEF-254261-BIO-DISTANCE" cannot be used as a page name in this wiki.
| Title | Periocular Recognition Using Retinotopic Sampling and Gabor Decomposition |
|---|---|
| Author | Fernando Alonso-Fernandez and Josef Bigun |
| Year | 2012 |
| PublicationType | Conference Paper |
| Journal | |
| HostPublication | Computer Vision -- ECCV 2012 : Workshops and demonstrations : Florence, Italy, October 7-13, 2012, Proceedings. Part II |
| Conference | International Workshop “What's in a Face?” WIAF, in conjunction with the 12th European Conference on Computer Vision, ECCV 2012, Florence, Italy, 7-13 October, 2012 |
| DOI | http://dx.doi.org/10.1007/978-3-642-33868-7_31 |
| Diva url | http://hh.diva-portal.org/smash/record.jsf?searchId=1&pid=diva2:545741 |
| Abstract | We present a new system for biometric recognition using periocular images based on retinotopic sampling grids and Gabor analysis of the local power spectrum. A number of aspects are studied, including: 1) grid adaptation to dimensions of the target eye vs. grids of constant size, 2) comparison between circular- and rectangular-shaped grids, 3) use of Gabor magnitude vs. phase vectors for recognition, 4) rotation compensation between query and test images, and 5) comparison with an iris machine expert. Results show that our system achieves competitive verification rates compared with other periocular recognition approaches. We also show that top verification rates can be obtained without rotation compensation, thus allowing to remove this step for computational efficiency. Also, the performance is not affected substantially if we use a grid of fixed dimensions, or it is even better in certain situations, avoiding the need of accurate detection of the iris region. © 2012 Springer-Verlag. |
