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Cross-spectrum thermal to visible face recognition based on cascaded image synthesis

 
: Mallat, Khawla; Damer, Naser; Boutros, Fadi; Kuijper, Arjan; Dugelay, Jean-Luc

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Institute of Electrical and Electronics Engineers -IEEE-; IEEE Computer Society; International Association for Pattern Recognition -IAPR-:
12th IAPR International Conference on Biometrics, ICB 2019 : 4-7 June 2019, Crete, Greece
Piscataway, NJ: IEEE, 2019
ISBN: 978-1-7281-3640-0
ISBN: 978-1-7281-3641-7
8 pp.
International Conference on Biometrics (ICB) <12, 2019, Crete>
European Commission EC
H2020; 870761; PROTECT
THE RIGHT TO INTERNATIONAL PROTECTION: A PENDULUM BETWEEN GLOBALIZATION AND NATIVIZATION?
English
Conference Paper
Fraunhofer IGD ()
CRISP; Lead Topic: Visual Computing as a Service; Research Line: Computer vision (CV); biometrics; biometric identification systems; face recognition

Abstract
Face synthesis from thermal to visible spectrum is fundamental to perform cross-spectrum face recognition as it simplifies its integration in existing commercial face recognition systems and enables manual face verification. In this paper, a new solution based on cascaded refinement networks is proposed. This method generates visible-like colored images of high visual quality without requiring large amounts of training data. By employing a contextual loss function during training, the proposed network is inherently scale and rotation invariant. We discuss the visual perception of the generated visible-like faces in comparison with recent works. We also provide an objective evaluation in terms of cross-spectrum face recognition, where the generated faces were compared against a gallery in visible spectrum using two state-of-the-art deep learning based face recognition systems. When compared to the recently published TV-GAN solution, the performance of the face recognition systems, OpenFace and LightCNN, was improved by a 42.48% (i.e. from 10.76% to 15.37%) and a 71.43% (i.e. from 33.606% to 57.612%), respectively.

: http://publica.fraunhofer.de/documents/N-578036.html