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A Study on Presentation Attack Detection in Thermal Infrared.

Marcin Kowalski1

  • 1Institute of Optoelectronics, Military University of Technology, 2 Gen. S. Kaliskiego St., 00-908 Warsaw, Poland.

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|July 26, 2020
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Thermal infrared imaging enhances face recognition by detecting sophisticated presentation attacks. This study introduces a new dataset and a deep learning method to improve spoof detection accuracy.

Keywords:
facial counter spoofingpresentation attack detectionthermal face spoofing detectionthermal infrared

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Area of Science:

  • Biometrics
  • Computer Vision
  • Infrared Imaging

Background:

  • Traditional face recognition systems struggle with advanced presentation attacks.
  • Sophisticated spoofing methods are increasingly difficult to detect.
  • Thermal infrared imaging offers unique properties for enhanced detection.

Purpose of the Study:

  • Investigate the detection of face presentation attacks using thermal infrared imaging.
  • Analyze various spoofing methods including masks and photographs under different conditions.
  • Evaluate the impact of thermalization and subject state on detection accuracy.

Main Methods:

  • Analysis of thermal energy distribution on facial landmarks.
  • Investigation of printed/displayed photographs, 3D-printed, 3D-latex, and silicone masks.
  • Development and validation of a two-step deep learning-based detection method.
  • Introduction of a novel thermal face spoofing dataset.

Main Results:

  • Demonstrated the effectiveness of thermal imaging in distinguishing real faces from various spoofing attempts.
  • Quantified thermalization impact and subject state variations on spoof detection.
  • Validated deep learning models on diverse presentation attack instruments using the new dataset.

Conclusions:

  • Thermal infrared imaging significantly improves the robustness of face recognition against presentation attacks.
  • The proposed deep learning approach and dataset offer a promising direction for advanced spoof detection.
  • Further research can leverage thermal data for more secure biometric systems.