Cross-Eyed 2017: Cross-Spectral Iris/Periocular Recognition Competition

被引：0

作者：

Sequeira, Ana F. ^{[1
]}

Chen, Lulu ^{[1
]}

Ferryman, James ^{[1
]}

Wild, Peter ^{[2
]}

Alonso-Fernandez, Fernando ^{[3
]}

Bigun, Josef ^{[3
]}

Raja, Kiran B. ^{[4
]}

Raghavendra, R. ^{[4
]}

Busch, Christoph ^{[4
]}

Pereira, Tiago de Freitas ^{[5
]}

Marcel, Sebastien ^{[5
]}

Behera, Sushree Sangeeta ^{[6
]}

Gour, Mahesh ^{[6
]}

Kanhangad, Vivek ^{[6
]}

机构：

[1] Univ Reading, Reading, Berks, England

[2] Tecan Austria GmbH, Grodig, Austria

[3] Halmstad Univ, Halmstad, Sweden

[4] NTNU, Norwegian Biometr Lab, Trondheim, Norway

[5] ldiap Res Inst, Martigny, Switzerland

[6] Indian Inst Technol Indore, Indore, Madhya Pradesh, India

来源：

2017 IEEE INTERNATIONAL JOINT CONFERENCE ON BIOMETRICS (IJCB) | 2017年

基金：

瑞士国家科学基金会; 欧盟地平线“2020”; 瑞典研究理事会;

关键词：

FEATURES; IRIS;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This 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.

引用

页码：725 / 732

页数：8

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