Thermal to visible face recognition

Jonghyun Choi, Shuowen Hu, S. Susan Young, Larry S. Davis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

41 Citations (Scopus)

Abstract

In low light conditions, visible light face identification is infeasible due to the lack of illumination. For nighttime surveillance, thermal imaging is commonly used because of the intrinsic emissivity of thermal radiation from the human body. However, matching thermal images of faces acquired at nighttime to the predominantly visible light face imagery in existing government databases and watch lists is a challenging task. The difficulty arises from the significant difference between the face's thermal signature and its visible signature (i.e. the modality gap). To match the thermal face to the visible face acquired by the two different modalities, we applied face recognition algorithms that reduce the modality gap in each step of face identification, from low-level analysis to machine learning techniques. Specifically, partial least squares-discriminant analysis (PLS-DA) based approaches were used to correlate the thermal face signatures to the visible face signatures, yielding a thermal-to-visible face identification rate of 49.9%. While this work makes progress for thermal-to-visible face recognition, more efforts need to be devoted to solving this difficult task. Successful development of a thermal-to-visible face recognition system would significantly enhance the Nation's nighttime surveillance capabilities.

Original languageEnglish
Title of host publicationSensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring II; and Biometric Technology for Human Identification IX
DOIs
Publication statusPublished - 2012
EventSensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring II; and Biometric Technology for Human Identification IX - Baltimore, MD, United States
Duration: 2012 Apr 232012 Apr 25

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8371
ISSN (Print)0277-786X

Conference

ConferenceSensing Technologies for Global Health, Military Medicine, Disaster Response, and Environmental Monitoring II; and Biometric Technology for Human Identification IX
Country/TerritoryUnited States
CityBaltimore, MD
Period12/4/2312/4/25

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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