Abstract
Development of facial recognition or expression recognition algorithms requires input data to thoroughly
test the performance of algorithms in various conditions. Researchers are developing various methods to
face challenges like illumination, pose and expression changes, as well as facial disguises. In this paper, we
propose and establish a dataset of thermal facial images, which contains a set of neutral images in various
poses as well as a set of facial images with different posed expressions collected with a thermal infrared
camera. Since the properties of face in the thermal domain strongly depend on time, in order to show the
impact of aging, collection of the dataset has been repeated and a corresponding set of data is provided.
The paper describes the measurement methodology and database structure. We present baseline results
of processing using state-of-the-art facial descriptors combined with distance metrics for thermal face reidentification.
Three selected local descriptors, a histogram of oriented gradients, local binary patterns and
local derivative patterns are used for elementary assessment of the database. The dataset offers a wide range
of capabilities – from thermal face recognition to thermal expression recognition.
Go to article