hh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
A survey on periocular biometrics research
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0002-1400-346X
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
2016 (English)In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 82, part 2, 92-105 p.Article in journal (Refereed) Published
Abstract [en]

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 emerged as a promising trait for unconstrained biometrics, following demands for increased robustness of face or iris systems. With a surprisingly high discrimination ability, this region can be easily obtained with existing setups for face and iris, and the requirement of user cooperation can be relaxed, thus facilitating the interaction with biometric systems. It is also available over a wide range of distances even when the iris texture cannot be reliably obtained (low resolution) or under partial face occlusion (close distances). Here, we review the state of the art in periocular biometrics research. A number of aspects are described, including: (i) existing databases, (ii) algorithms for periocular detection and/or segmentation, (iii) features employed for recognition, (iv) identification of the most discriminative regions of the periocular area, (v) comparison with iris and face modalities, (vi) soft-biometrics (gender/ethnicity classification), and (vii) impact of gender transformation and plastic surgery on the recognition accuracy. This work is expected to provide an insight of the most relevant issues in periocular biometrics, giving a comprehensive coverage of the existing literature and current state of the art. © 2015 Elsevier B.V. All rights reserved.

Place, publisher, year, edition, pages
Amsterdam: Elsevier, 2016. Vol. 82, part 2, 92-105 p.
Keyword [en]
Periocular, Biometrics, Iris, Eye, Face
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:hh:diva-29812DOI: 10.1016/j.patrec.2015.08.026Scopus ID: 2-s2.0-84950261580OAI: oai:DiVA.org:hh-29812DiVA: diva2:873743
Funder
Swedish Research Council, 2012-4313Knowledge Foundation
Note

Author F. A.-F. thanks the Swedish Research Council grant 2012-4313 and the Marie-Curie IEF grant 254261 for funding his research. Authors acknowledge the CAISR program of the Swedish Knowledge Foundation and the EU COST Action IC1106.

Available from: 2015-11-24 Created: 2015-11-24 Last updated: 2016-11-03Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Search in DiVA

By author/editor
Alonso-Fernandez, FernandoBigun, Josef
By organisation
CAISR - Center for Applied Intelligent Systems Research
In the same journal
Pattern Recognition Letters
Signal Processing

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 244 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf