International Journal of Computer Vision

, Volume 71, Issue 2, pp 197–214 | Cite as

Imaging Facial Physiology for the Detection of Deceit

  • P. TsiamyrtzisEmail author
  • J. Dowdall
  • D. Shastri
  • I. T. Pavlidis
  • M. G. Frank
  • P. Ekman


Previous work has demonstrated the correlation of increased blood perfusion in the orbital muscles and stress levels for human beings. It has also been suggested that this periorbital perfusion can be quantified through the processing of thermal video. The idea has been based on the fact that skin temperature is heavily modulated by superficial blood flow. Proof of this concept was established for two different types of stress inducing experiments: startle experiments and mock-crime polygraph interrogations. However, the polygraph interrogation scenarios were simplistic and highly constrained. In the present paper, we report results derived from a large and realistic mock-crime interrogation experiment. The interrogation is free flowing and no restrictions have been placed on the subjects. Additionally, we propose a new methodology to compute the mean periorbital temperature signal. The present approach addresses the deficiencies of the earlier methodology and is capable of coping with the challenges posed by the realistic setting. Specifically, it features a tandem CONDENSATION tracker to register the periorbital area in the context of a moving face. It operates on the raw temperature signal and tries to improve the information content by suppressing the noise level instead of amplifying the signal as a whole. Finally, a pattern recognition method classifies stressful (Deceptive) from non-stressful (Non-Deceptive) subjects based on a comparative measure between the entire interrogation signal (baseline) and a critical subsection of it (transient response). The successful classification rate is 87.2% for 39 subjects. This is on par with the success rate achieved by highly trained psycho-physiological experts and opens the way for automating lie detection in realistic settings.


deception detection polygraph thermography facial tracking contact-free physiological monitoring 


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Copyright information

© Springer Science + Business Media, LLC 2006

Authors and Affiliations

  • P. Tsiamyrtzis
    • 1
    Email author
  • J. Dowdall
    • 2
  • D. Shastri
    • 2
  • I. T. Pavlidis
    • 2
  • M. G. Frank
    • 3
  • P. Ekman
    • 4
  1. 1.Department of StatisticsAthens University of Economics and BusinessAthensGreece
  2. 2.Department of Computer ScienceUniversity of HoustonHouston
  3. 3.School of Informatics/Department of CommunicationUniversity of Buffalo, State University of New YorkBuffalo
  4. 4.Department of PsychiatryUC San FranciscoSan Francisco

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