Please use this identifier to cite or link to this item: https://dspace.iiti.ac.in/handle/123456789/5263
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dc.contributor.authorKanhangad, Viveken_US
dc.date.accessioned2022-03-17T01:00:00Z-
dc.date.accessioned2022-03-17T15:39:10Z-
dc.date.available2022-03-17T01:00:00Z-
dc.date.available2022-03-17T15:39:10Z-
dc.date.issued2018-
dc.identifier.citationSequeira, A. F., Chen, L., Ferryman, J., Wild, P., Alonso-Fernandez, F., Bigun, J., . . . Kanhangad, V. (2018). Cross-eyed 2017: Cross-spectral iris/periocular recognition competition. Paper presented at the IEEE International Joint Conference on Biometrics, IJCB 2017, , 2018-January 725-732. doi:10.1109/BTAS.2017.8272762en_US
dc.identifier.isbn9781538611241-
dc.identifier.otherEID(2-s2.0-85046282830)-
dc.identifier.urihttps://doi.org/10.1109/BTAS.2017.8272762-
dc.identifier.urihttps://dspace.iiti.ac.in/handle/123456789/5263-
dc.description.abstractThis work presents the 2nd Cross-Spectrum Iris/Periocular Recognition Competition (Cross-Eyed2017). The main goal of the competition is to promote and evaluate advances in cross-spectrum iris and periocular recognition. This second edition registered an increase in the participation numbers ranging from academia to industry: five teams submitted twelve methods for the periocular task and five for the iris task. The benchmark dataset is an enlarged version of the dual-spectrum database containing both iris and periocular images synchronously captured from a distance and within a realistic indoor environment. The evaluation was performed on an undisclosed test-set. Methodology, tested algorithms, and obtained results are reported in this paper identifying the remaining challenges in path forward. © 2017 IEEE.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceIEEE International Joint Conference on Biometrics, IJCB 2017en_US
dc.subjectSpectroscopyen_US
dc.subjectBenchmark datasetsen_US
dc.subjectCross spectraen_US
dc.subjectIndoor environmenten_US
dc.subjectPeriocularen_US
dc.subjectPeriocular recognitionen_US
dc.subjectTest setsen_US
dc.subjectBiometricsen_US
dc.titleCross-eyed 2017: Cross-spectral iris/periocular recognition competitionen_US
dc.typeConference Paperen_US
dc.rights.licenseAll Open Access, Green-
Appears in Collections:Department of Electrical Engineering

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