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Differential 3D Facial Recognition: Adding 3D to Your State-of-the-Art 2D Method.

Publication ,  Journal Article
Martino, JMD; Suzacq, F; Delbracio, M; Qiu, Q; Sapiro, G
Published in: IEEE transactions on pattern analysis and machine intelligence
July 2020

Active illumination is a prominent complement to enhance 2D face recognition and make it more robust, e.g., to spoofing attacks and low-light conditions. In the present work we show that it is possible to adopt active illumination to enhance state-of-the-art 2D face recognition approaches with 3D features, while bypassing the complicated task of 3D reconstruction. The key idea is to project over the test face a high spatial frequency pattern, which allows us to simultaneously recover real 3D information plus a standard 2D facial image. Therefore, state-of-the-art 2D face recognition solution can be transparently applied, while from the high frequency component of the input image, complementary 3D facial features are extracted. Experimental results on ND-2006 dataset show that the proposed ideas can significantly boost face recognition performance and dramatically improve the robustness to spoofing attacks.

Duke Scholars

Published In

IEEE transactions on pattern analysis and machine intelligence

DOI

EISSN

1939-3539

ISSN

0162-8828

Publication Date

July 2020

Volume

42

Issue

7

Start / End Page

1582 / 1593

Related Subject Headings

  • Imaging, Three-Dimensional
  • Humans
  • Face
  • Databases, Factual
  • Computer Security
  • Automated Facial Recognition
  • Artificial Intelligence & Image Processing
  • Algorithms
  • 4611 Machine learning
  • 4603 Computer vision and multimedia computation
 

Citation

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MLA
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Martino, J. M. D., Suzacq, F., Delbracio, M., Qiu, Q., & Sapiro, G. (2020). Differential 3D Facial Recognition: Adding 3D to Your State-of-the-Art 2D Method. IEEE Transactions on Pattern Analysis and Machine Intelligence, 42(7), 1582–1593. https://doi.org/10.1109/tpami.2020.2986951
Martino, J Matias Di, Fernando Suzacq, Mauricio Delbracio, Qiang Qiu, and Guillermo Sapiro. “Differential 3D Facial Recognition: Adding 3D to Your State-of-the-Art 2D Method.IEEE Transactions on Pattern Analysis and Machine Intelligence 42, no. 7 (July 2020): 1582–93. https://doi.org/10.1109/tpami.2020.2986951.
Martino JMD, Suzacq F, Delbracio M, Qiu Q, Sapiro G. Differential 3D Facial Recognition: Adding 3D to Your State-of-the-Art 2D Method. IEEE transactions on pattern analysis and machine intelligence. 2020 Jul;42(7):1582–93.
Martino, J. Matias Di, et al. “Differential 3D Facial Recognition: Adding 3D to Your State-of-the-Art 2D Method.IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 42, no. 7, July 2020, pp. 1582–93. Epmc, doi:10.1109/tpami.2020.2986951.
Martino JMD, Suzacq F, Delbracio M, Qiu Q, Sapiro G. Differential 3D Facial Recognition: Adding 3D to Your State-of-the-Art 2D Method. IEEE transactions on pattern analysis and machine intelligence. 2020 Jul;42(7):1582–1593.

Published In

IEEE transactions on pattern analysis and machine intelligence

DOI

EISSN

1939-3539

ISSN

0162-8828

Publication Date

July 2020

Volume

42

Issue

7

Start / End Page

1582 / 1593

Related Subject Headings

  • Imaging, Three-Dimensional
  • Humans
  • Face
  • Databases, Factual
  • Computer Security
  • Automated Facial Recognition
  • Artificial Intelligence & Image Processing
  • Algorithms
  • 4611 Machine learning
  • 4603 Computer vision and multimedia computation