Human thermal modeling to augment MWIR image analysis in surveillance applications

R. L. Woodyard; J. A. Skipper

doi:10.1117/12.2050654

29 May 2014 Human thermal modeling to augment MWIR image analysis in surveillance applications

R. L. Woodyard, J. A. Skipper

Proceedings Volume 9075, Biometric and Surveillance Technology for Human and Activity Identification XI; 90750B (2014) https://doi.org/10.1117/12.2050654
Event: SPIE Defense + Security, 2014, Baltimore, MD, United States

Abstract

The interpretation of thermal imagery can be augmented with information derived from human thermal modeling to better infer human activity during, or prior to, data capture. This additional insight into human activity could prove useful in security and surveillance applications. We have implemented Tanabe’s 65 NM thermocomfort model to predict skin surface temperature under a wide variety of environmental, activity and body parameters. Here, humans are modeled as sixteen segments (head, chest, upper leg, etc.), wherein spherical geometry is assumed for the head and cylindrical geometry is assumed for all other segments. Each segment is comprised of four layers: core, muscle, fat, and skin. Clothing is modeled as an additional layer (or layers) of resistance. Users supply input parameters via our custom MATLAB graphical user interface that includes a robust clothing database based on McCullough’s A Database for Determining the Evaporative Resistance of Clothing, and then Tanabe’s bioheat equations are solved to predict skin temperatures of each body segment. As an initial step of model validation, we compared our computed thermal resistances with literature values. Our evaporative and dry resistance on a per segment basis agreed with literature values. The dry resistance of each segment varied no more than .03 [m2°C/W]. Model validation will be extended to compare the results of our human subject trials (known body parameters, clothing, environmental factors and activity levels) to model outputs. Agreement would further substantiate the propagation of model- predicted skin temperatures through the thermal imager’s transfer function to predict human heat signatures in thermal imagery.

Citation Download Citation

R. L. Woodyard and J. A. Skipper "Human thermal modeling to augment MWIR image analysis in surveillance applications", Proc. SPIE 9075, Biometric and Surveillance Technology for Human and Activity Identification XI, 90750B (29 May 2014); https://doi.org/10.1117/12.2050654

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KEYWORDS

Skin

Resistance

Thermal modeling

Head

Temperature metrology

Blood circulation

Thermography

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