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Z. Boulkenafet et al., "A competition on generalized software-based face presentation attack detection in mobile scenarios," 2017 IEEE International Joint Conference on Biometrics (IJCB), Denver, CO, 2017, pp. 688-696. doi: 10.1109/BTAS.2017.8272758

A competition on generalized software-based face presentation attack detection in mobile scenarios

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Author: Boulkenafet, Z.1; Komulainen, J.1; Akhtar, Z.2;
Organizations: 1University of Oulu (FI)
2INRS-EMT, University of Quebec (CA)
3University of Ouargla (DZ)
4University of Biskra (DZ)
5University of the Basque Country (ES)
6University of Valenciennes (FR)
7Hunan University (CN)
8Changsha University of Science and Technology (CN)
9Indian Institute of Technology Indore (IN)
10GRADIANT (ES)
11Ecole Polytechnique Federale de Lausanne (CH)
12Idiap Research Institute (CH)
13Vologda State University (RU)
14Shenzhen University (CN)
15FUJITSU LABORATORIES LTD LTD (JP)
16Northwestern Polytechnical University (CN)
17Hong Kong Baptist University (HK)
18University of Campinas (BR)
19CPqD (BR)
20CPqD (BR).
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.9 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019091228006
Language: English
Published: Institute of Electrical and Electronics Engineers, 2017
Publish Date: 2019-09-12
Description:

Abstract

In recent years, software-based face presentation attack detection (PAD) methods have seen a great progress. However, most existing schemes are not able to generalize well in more realistic conditions. The objective of this competition is to evaluate and compare the generalization performances of mobile face PAD techniques under some real-world variations, including unseen input sensors, presentation attack instruments (PAI) and illumination conditions, on a larger scale OULU-NPU dataset using its standard evaluation protocols and metrics. Thirteen teams from academic and industrial institutions across the world participated in this competition. This time typical liveness detection based on physiological signs of life was totally discarded. Instead, every submitted system relies practically on some sort of feature representation extracted from the face and/or background regions using hand-crafted, learned or hybrid descriptors. Interesting results and findings are presented and discussed in this paper.

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Series: IEEE International Conference on Biometrics, Theory, Applications and Systems
ISSN: 2474-9680
ISSN-E: 2474-9699
ISSN-L: 2474-9680
ISBN: 978-1-5386-1124-1
ISBN Print: 978-1-5386-1125-8
Pages: 688 - 696
DOI: 10.1109/BTAS.2017.8272758
OADOI: https://oadoi.org/10.1109/BTAS.2017.8272758
Host publication: 2017 IEEE International Joint Conference on Biometrics (IJCB)
Conference: IEEE International Joint Conference on Biometrics
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
113 Computer and information sciences
Subjects:
Article
Funding: The financial support of the Academy of Finland, In-fotech Oulu, the Nokia Foundation and the Finnish Foundation for Technology Promotion is fully acknowledged.
Copyright information: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.