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

Z. Boulkenafet; J. Komulainen; Z. Akhtar; A. Benlamoudi; D. Samai; S. E. Bekhouche; A. Ouafi; F. Dornaika; A. Taleb-Ahmed; L. Qin; F. Peng; L. B. Zhang; M. Long; S. Bhilare; V. Kanhangad; A. Costa-Pazo; E. Vazquez-Fernandez; D. Pérez-Cabo; J. J. Moreira-Pérez; D. González-Jiménez; A. Mohammadi; S. Bhattacharjee; S. Marcel; S. Volkova; Y. Tang; N. Abe; L. Li; X. Feng; Z. Xia; X. Jiang; S. Liu; R. Shao; P. C. Yuen; W. R. Almeida; F. Andaló; R. Padilha; G. Bertocco; W. Dias; J. Wainer; R. Torres; A. Rocha; M. A. Angeloni; G. Folego; A. Godoy; A. Hadid

doi:10.1109/BTAS.2017.8272758

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

Z. Boulkenafet, J. Komulainen, Z. Akhtar, A. Benlamoudi, D. Samai, S. E. Bekhouche, A. Ouafi, F. Dornaika, A. Taleb-Ahmed, L. Qin, F. Peng, L. B. Zhang, M. Long, S. Bhilare, V. Kanhangad, A. Costa-Pazo, E. Vazquez-Fernandez, D. Pérez-Cabo, J. J. Moreira-Pérez, D. González-JiménezA. Mohammadi, S. Bhattacharjee, S. Marcel, S. Volkova, Y. Tang, N. Abe, L. Li, X. Feng, Z. Xia, X. Jiang, S. Liu, R. Shao, P. C. Yuen, W. R. Almeida, F. Andaló, R. Padilha, G. Bertocco, W. Dias, J. Wainer, R. Torres, A. Rocha, M. A. Angeloni, G. Folego, A. Godoy, A. Hadid

Department of Computer Science

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

119 Citations (Scopus)

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.

Original language	English
Title of host publication	IEEE International Joint Conference on Biometrics, IJCB 2017
Publisher	IEEE
Pages	688-696
Number of pages	9
ISBN (Electronic)	9781538611241
DOIs	https://doi.org/10.1109/BTAS.2017.8272758
Publication status	Published - 1 Jul 2017
Event	2017 IEEE International Joint Conference on Biometrics, IJCB 2017 - Denver, United States Duration: 1 Oct 2017 → 4 Oct 2017

Publication series

Name	IEEE International Joint Conference on Biometrics, IJCB 2017
Volume	2018-January

Conference

Conference	2017 IEEE International Joint Conference on Biometrics, IJCB 2017
Country/Territory	United States
City	Denver
Period	1/10/17 → 4/10/17

Scopus Subject Areas

Computer Networks and Communications
Instrumentation
Signal Processing
Biomedical Engineering

Access to Document

10.1109/BTAS.2017.8272758

Cite this

Boulkenafet, Z., Komulainen, J., Akhtar, Z., Benlamoudi, A., Samai, D., Bekhouche, S. E., Ouafi, A., Dornaika, F., Taleb-Ahmed, A., Qin, L., Peng, F., Zhang, L. B., Long, M., Bhilare, S., Kanhangad, V., Costa-Pazo, A., Vazquez-Fernandez, E., Pérez-Cabo, D., Moreira-Pérez, J. J., ... Hadid, A. (2017). A competition on generalized software-based face presentation attack detection in mobile scenarios. In IEEE International Joint Conference on Biometrics, IJCB 2017 (pp. 688-696). (IEEE International Joint Conference on Biometrics, IJCB 2017; Vol. 2018-January). IEEE. https://doi.org/10.1109/BTAS.2017.8272758

@inproceedings{ae226d42e2c14a1d8015d1be9ca4870d,

title = "A competition on generalized software-based face presentation attack detection in mobile scenarios",

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.",

author = "Z. Boulkenafet and J. Komulainen and Z. Akhtar and A. Benlamoudi and D. Samai and Bekhouche, {S. E.} and A. Ouafi and F. Dornaika and A. Taleb-Ahmed and L. Qin and F. Peng and Zhang, {L. B.} and M. Long and S. Bhilare and V. Kanhangad and A. Costa-Pazo and E. Vazquez-Fernandez and D. P{\'e}rez-Cabo and Moreira-P{\'e}rez, {J. J.} and D. Gonz{\'a}lez-Jim{\'e}nez and A. Mohammadi and S. Bhattacharjee and S. Marcel and S. Volkova and Y. Tang and N. Abe and L. Li and X. Feng and Z. Xia and X. Jiang and S. Liu and R. Shao and Yuen, {P. C.} and Almeida, {W. R.} and F. Andal{\'o} and R. Padilha and G. Bertocco and W. Dias and J. Wainer and R. Torres and A. Rocha and Angeloni, {M. A.} and G. Folego and A. Godoy and A. Hadid",

note = "Funding Information: The financial support of the Academy of Finland, In-fotech Oulu, the Nokia Foundation and the Finnish Foundation for Technology Promotion is fully acknowledged.; 2017 IEEE International Joint Conference on Biometrics, IJCB 2017 ; Conference date: 01-10-2017 Through 04-10-2017",

year = "2017",

month = jul,

day = "1",

doi = "10.1109/BTAS.2017.8272758",

language = "English",

series = "IEEE International Joint Conference on Biometrics, IJCB 2017",

publisher = "IEEE",

pages = "688--696",

booktitle = "IEEE International Joint Conference on Biometrics, IJCB 2017",

address = "United States",

}

Boulkenafet, Z, Komulainen, J, Akhtar, Z, Benlamoudi, A, Samai, D, Bekhouche, SE, Ouafi, A, Dornaika, F, Taleb-Ahmed, A, Qin, L, Peng, F, Zhang, LB, Long, M, Bhilare, S, Kanhangad, V, Costa-Pazo, A, Vazquez-Fernandez, E, Pérez-Cabo, D, Moreira-Pérez, JJ, González-Jiménez, D, Mohammadi, A, Bhattacharjee, S, Marcel, S, Volkova, S, Tang, Y, Abe, N, Li, L, Feng, X, Xia, Z, Jiang, X, Liu, S, Shao, R, Yuen, PC, Almeida, WR, Andaló, F, Padilha, R, Bertocco, G, Dias, W, Wainer, J, Torres, R, Rocha, A, Angeloni, MA, Folego, G, Godoy, A & Hadid, A 2017, A competition on generalized software-based face presentation attack detection in mobile scenarios. in IEEE International Joint Conference on Biometrics, IJCB 2017. IEEE International Joint Conference on Biometrics, IJCB 2017, vol. 2018-January, IEEE, pp. 688-696, 2017 IEEE International Joint Conference on Biometrics, IJCB 2017, Denver, United States, 1/10/17. https://doi.org/10.1109/BTAS.2017.8272758

A competition on generalized software-based face presentation attack detection in mobile scenarios. / Boulkenafet, Z.; Komulainen, J.; Akhtar, Z. et al.
IEEE International Joint Conference on Biometrics, IJCB 2017. IEEE, 2017. p. 688-696 (IEEE International Joint Conference on Biometrics, IJCB 2017; Vol. 2018-January).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - A competition on generalized software-based face presentation attack detection in mobile scenarios

AU - Boulkenafet, Z.

AU - Komulainen, J.

AU - Akhtar, Z.

AU - Benlamoudi, A.

AU - Samai, D.

AU - Bekhouche, S. E.

AU - Ouafi, A.

AU - Dornaika, F.

AU - Taleb-Ahmed, A.

AU - Qin, L.

AU - Peng, F.

AU - Zhang, L. B.

AU - Long, M.

AU - Bhilare, S.

AU - Kanhangad, V.

AU - Costa-Pazo, A.

AU - Vazquez-Fernandez, E.

AU - Pérez-Cabo, D.

AU - Moreira-Pérez, J. J.

AU - González-Jiménez, D.

AU - Mohammadi, A.

AU - Bhattacharjee, S.

AU - Marcel, S.

AU - Volkova, S.

AU - Tang, Y.

AU - Abe, N.

AU - Li, L.

AU - Feng, X.

AU - Xia, Z.

AU - Jiang, X.

AU - Liu, S.

AU - Shao, R.

AU - Yuen, P. C.

AU - Almeida, W. R.

AU - Andaló, F.

AU - Padilha, R.

AU - Bertocco, G.

AU - Dias, W.

AU - Wainer, J.

AU - Torres, R.

AU - Rocha, A.

AU - Angeloni, M. A.

AU - Folego, G.

AU - Godoy, A.

AU - Hadid, A.

N1 - Funding Information: The financial support of the Academy of Finland, In-fotech Oulu, the Nokia Foundation and the Finnish Foundation for Technology Promotion is fully acknowledged.

PY - 2017/7/1

Y1 - 2017/7/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85046265698&partnerID=8YFLogxK

U2 - 10.1109/BTAS.2017.8272758

DO - 10.1109/BTAS.2017.8272758

M3 - Conference proceeding

AN - SCOPUS:85046265698

T3 - IEEE International Joint Conference on Biometrics, IJCB 2017

SP - 688

EP - 696

BT - IEEE International Joint Conference on Biometrics, IJCB 2017

PB - IEEE

T2 - 2017 IEEE International Joint Conference on Biometrics, IJCB 2017

Y2 - 1 October 2017 through 4 October 2017

ER -

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

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