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) › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Title of host publication | International Joint Conference |
Subtitle of host publication | 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019), Proceedings |
Editors | Francisco Martínez Álvarez, Alicia Troncoso Lora, José António Sáez Muñoz, Héctor Quintián, Emilio Corchado |
Publisher | Springer, Cham |
Pages | 3-13 |
Volume | 951 |
ISBN (Electronic) | 978-3-030-20005-3 |
ISBN (Print) | 978-3-030-20004-6 |
Publication status | Published - May 2019 |
Publication series
Name | Advances in Intelligent Systems and Computing |
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Volume | 951 |
ISSN (Print) | 2194-5357 |
Conference
Title | 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 |
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Place | Spain |
City | Seville |
Period | 13 - 15 May 2019 |
Link(s)
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 et al.
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) › peer-review