Perturbing Convolutional Feature Maps with Histogram of Oriented Gradients for Face Liveness Detection

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)

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Detail(s)

Original languageEnglish
Title of host publicationInternational Joint Conference
Subtitle of host publication12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019), Proceedings
EditorsFrancisco Martínez Álvarez, Alicia Troncoso Lora, José António Sáez Muñoz, Héctor Quintián, Emilio Corchado
PublisherSpringer, Cham
Pages3-13
Volume951
ISBN (Electronic)978-3-030-20005-3
ISBN (Print)978-3-030-20004-6
Publication statusPublished - May 2019

Publication series

NameAdvances in Intelligent Systems and Computing
Volume951
ISSN (Print)2194-5357

Conference

TitleInternational Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems, CISIS 2019 and 10th International Conference on European Transnational Education, ICEUTE 2019
PlaceSpain
CitySeville
Period13 - 15 May 2019

Abstract

Face anti-spoofing in unconstrained environment is one of the key issues in face biometric based authentication and security applications. To minimize the false alarms in face anti-spoofing tests, this paper proposes a novel approach to learn perturbed feature maps by perturbing the convolutional feature maps with Histogram of Oriented Gradients (HOG) features. The perturbed feature maps are learned simultaneously during training of Convolution Neural Network (CNN) for face anti-spoofing, in an end-to-end fashion. Extensive experiments are performed on state-of-the-art face anti-spoofing databases, like OULU-NPU, CASIA-FASD and Replay-Attack, in both intra-database and cross-database scenarios. Experimental results indicate that the proposed framework perform significantly better compare to previous state-of-the-art approaches in both intra-database and cross-database face anti-spoofing scenarios.

Research Area(s)

  • Convolution Neural Networks, Face liveness detection, Histogram of Oriented Gradients

Citation Format(s)

Perturbing Convolutional Feature Maps with Histogram of Oriented Gradients for Face Liveness Detection. / Rehman, Yasar Abbas Ur; Po, Lai-Man; Liu, Mengyang; Zou, Zijie; Ou, Weifeng.

International Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019), Proceedings. ed. / Francisco Martínez Álvarez; Alicia Troncoso Lora; José António Sáez Muñoz; Héctor Quintián; Emilio Corchado. Vol. 951 Springer, Cham, 2019. p. 3-13 (Advances in Intelligent Systems and Computing; Vol. 951).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)