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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.
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Authors and Affiliations

Marcin Kowalski
Artur Grudzień
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Abstract

The presented study concerns development of a facial detection algorithm operating robustly in the thermal infrared spectrum. The paper presents a brief review of existing face detection algorithms, describes the experiment methodology and selected algorithms. For the comparative study of facial detection three methods presenting three different approaches were chosen, namely the Viola–Jones, YOLOv2 and Faster-RCNN. All these algorithms were investigated along with various configurations and parameters and evaluated using three publicly available thermal face datasets. The comparison of the original results of various experiments for the selected algorithms is presented.
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Authors and Affiliations

Marcin Ł. Kowalski
1
Artur Grudzien
1
Wiesław Ciurapinski
1

  1. Military University of Technology, Institute of Optoelectronics, gen. Sylwestra Kaliskiego 2, 00-908 Warszawa, Poland
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Abstract

This paper presents a study on the influence of psychophysical stimuli on facial thermal emissions. Two independent groups of stimuli are proposed to investigate facial changes resulting from human stress and physical exhaustion. One pertains to physical effort while the other is linked to stress invoked by solving a simple written test. Subjects’ face reactions were measured through collecting and analysing long-wavelength infrared images. A methodology for numerical processing of images is proposed. Results of numerical analysis with respect to different facial regions of interest are provided. An automatic deep learning based algorithm to classify specific thermal face patterns is proposed. The algorithm consists of detection of regions of interests as well as numerical analysis of thermal energy emissions of facial parts. The results of presented experiments allowed the authors to associate emission changes in specific facial regions with psychophysical stimulations of the person being examined. This work proves high usability of thermal imaging to capture changes of heat distribution of face as reactions for external stimuli.

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Authors and Affiliations

Jarosław Panasiuk
Piotr Prusaczyk
Artur Grudzień
Marcin Kowalski

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