Peter Wei
Xiaofan Jiang
ABSTRACT
With the recent societal impact of COVID-19, businesses and government agencies have turned to thermal camera based skin temperature sensing technology to help detect affected civilians. However, cost and deployment restrictions limit the widespread use of these thermal sensing technologies. In this work, we present a low cost system based on an RGB-thermal camera for continuously detecting and estimating facial temperature features for multiple people. This system detects and tracks heads in the RGB and thermal domains, constructs temperature models of individual facial features, and models environmental and surface effects on thermal sensing to reduce temperature measurement error.
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Low-cost multi-person continuous skin temperature sensing system for fever detection: poster abstract
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