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Compact Multi-scale Periocular Recognition Using SAFE Features
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).ORCID-id: 0000-0002-1400-346X
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).ORCID-id: 0000-0002-4929-1262
2017 (Engelska)Ingår i: Proceedings of the 23rd International Conference On Pattern Recognition (Icpr), IEEE Computer Society, 2017, s. 1455-1460, artikel-id 7899842Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

In this paper, we present a new approach for periocular recognition based on the Symmetry Assessment by Feature Expansion (SAFE) descriptor, which encodes the presence of various symmetric curve families around image key points. We use the sclera center as single key point for feature extraction, highlighting the object-like identity properties that concentrates to this unique point of the eye. As it is demonstrated, such discriminative properties can be encoded with a reduced set of symmetric curves. Experiments are done with a database of periocular images captured with a digital camera. We test our system against reference periocular features, achieving top performance with a considerably smaller feature vector (given by the use of a single key point). All the systems tested also show a nearly steady correlation between acquisition distance and performance, and they are also able to cope well when enrolment and test images are not captured at the same distance. Fusion experiments among the available systems are also provided. © 2016 IEEE.

Ort, förlag, år, upplaga, sidor
IEEE Computer Society, 2017. s. 1455-1460, artikel-id 7899842
Serie
International Conference on Pattern Recognition, ISSN 1051-4651
Nationell ämneskategori
Datorseende och robotik (autonoma system)
Identifikatorer
URN: urn:nbn:se:hh:diva-35644DOI: 10.1109/ICPR.2016.7899842ISI: 000406771301077Scopus ID: 2-s2.0-85019080000ISBN: 978-1-5090-4847-2 (tryckt)OAI: oai:DiVA.org:hh-35644DiVA, id: diva2:1163482
Konferens
23rd International Conference on Pattern Recognition (ICPR), Dec 4-8, 2016, Cancun, Mexico
Tillgänglig från: 2017-12-07 Skapad: 2017-12-07 Senast uppdaterad: 2018-01-13Bibliografiskt granskad

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Alonso-Fernandez, FernandoMikaelyan, AnnaBigun, Josef
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CAISR Centrum för tillämpade intelligenta system (IS-lab)Halmstad Embedded and Intelligent Systems Research (EIS)
Datorseende och robotik (autonoma system)

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