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Infrared Face Recognition by Using Blood Perfusion Data

  • Shi-Qian Wu
  • W. Song
  • Li-Jun Jiang
  • S. -L. Xie
  • Feng Pan
  • Wei-Yun Yau
  • Surendra Ranganath
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3546)

Abstract

This paper presents a blood perfusion model of human faces based on thermodynamics and thermal physiology. The target is to convert the facial temperature data which are liable to ambient temperature into consistent blood perfusion data in order to improve the performance of infrared (IR) face recognition. Our large number of experiments has demonstrated that the blood perfusion data are less sensitive to ambient temperature if the human bodies are in steady state, and the real data testing demonstrated that the performance by means of blood perfusion data is significantly superior to that via temperature data in terms of recognition rate.

Keywords

Face Recognition Recognition Rate Radial Basis Function Neural Network Blood Perfusion Temperature Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Shi-Qian Wu
    • 1
  • W. Song
    • 2
  • Li-Jun Jiang
    • 1
  • S. -L. Xie
    • 1
  • Feng Pan
    • 1
  • Wei-Yun Yau
    • 1
  • Surendra Ranganath
    • 2
  1. 1.Institute for Infocomm ResearchSingapore
  2. 2.Department of Electrical and Computer EngineeringNational University of SingaporeSingapore

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