Closed-set thermal face recognition via the synthesis approach

Oren Girshkin, Yitzhak Yitzhaky

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Thermal face recognition has various applications in security, video-surveillance, military and government industries, etc. In contrast to the visible-light domain case, there is a lack of sufficiently large databases of thermal-face images. Therefore, it is difficult to construct a good face recognition system directly through learning procedures. We address this problem by using the synthesis approach, in which artificial visible-domain images of faces are generated from thermal face images and then identified in the visible-light domain. The generation of the artificial face images is done using a conditional Generative Adversarial Network, and the face identification is done by another, separate, deep neural network. Generating visible face images from thermal ones using DNNs requires large datasets of pairs of thermal and visible face images of the same persons, taken from the same position, time and imaging conditions, with two different cameras. The available datasets of such pairs are of relatively very low amount of subjects. Therefore, as in other similar studies, we approach this problem as a closed-set face recognition task, in which all testing identities are predefined in the training set, and train the face identification network using both the real and the synthesized images.

Original languageEnglish
Title of host publicationCounterterrorism, Crime Fighting, Forensics, and Surveillance Technologies V
EditorsH. Bouma, R. Prabhu, R. J. Stokes, Y. Yitzhaky
PublisherSPIE
ISBN (Electronic)9781510645820
DOIs
StatePublished - 1 Jan 2021
EventCounterterrorism, Crime Fighting, Forensics, and Surveillance Technologies V 2021 - Virtual, Online, Spain
Duration: 13 Sep 202117 Sep 2021

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11869
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceCounterterrorism, Crime Fighting, Forensics, and Surveillance Technologies V 2021
Country/TerritorySpain
CityVirtual, Online
Period13/09/2117/09/21

Keywords

  • Conditional generative adversarial network
  • Thermal face recognition
  • Thermal-to visible synthesis

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