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A Modular System for Detection, Tracking and Analysis of Human Faces in Thermal Infrared Recordings †

We present a system that utilizes a range of image processing algorithms to allow fully automated thermal face analysis under both laboratory and real-world conditions. We implement methods for face detection, facial landmark detection, face frontalization and analysis, combining all of these into a...

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Detalles Bibliográficos
Autores principales: Kopaczka, Marcin, Breuer, Lukas, Schock, Justus, Merhof, Dorit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806182/
https://www.ncbi.nlm.nih.gov/pubmed/31554260
http://dx.doi.org/10.3390/s19194135
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author Kopaczka, Marcin
Breuer, Lukas
Schock, Justus
Merhof, Dorit
author_facet Kopaczka, Marcin
Breuer, Lukas
Schock, Justus
Merhof, Dorit
author_sort Kopaczka, Marcin
collection PubMed
description We present a system that utilizes a range of image processing algorithms to allow fully automated thermal face analysis under both laboratory and real-world conditions. We implement methods for face detection, facial landmark detection, face frontalization and analysis, combining all of these into a fully automated workflow. The system is fully modular and allows implementing own additional algorithms for improved performance or specialized tasks. Our suggested pipeline contains a histogtam of oriented gradients support vector machine (HOG-SVM) based face detector and different landmark detecion methods implemented using feature-based active appearance models, deep alignment networks and a deep shape regression network. Face frontalization is achieved by utilizing piecewise affine transformations. For the final analysis, we present an emotion recognition system that utilizes HOG features and a random forest classifier and a respiratory rate analysis module that computes average temperatures from an automatically detected region of interest. Results show that our combined system achieves a performance which is comparable to current stand-alone state-of-the-art methods for thermal face and landmark datection and a classification accuracy of 65.75% for four basic emotions.
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spelling pubmed-68061822019-11-07 A Modular System for Detection, Tracking and Analysis of Human Faces in Thermal Infrared Recordings † Kopaczka, Marcin Breuer, Lukas Schock, Justus Merhof, Dorit Sensors (Basel) Article We present a system that utilizes a range of image processing algorithms to allow fully automated thermal face analysis under both laboratory and real-world conditions. We implement methods for face detection, facial landmark detection, face frontalization and analysis, combining all of these into a fully automated workflow. The system is fully modular and allows implementing own additional algorithms for improved performance or specialized tasks. Our suggested pipeline contains a histogtam of oriented gradients support vector machine (HOG-SVM) based face detector and different landmark detecion methods implemented using feature-based active appearance models, deep alignment networks and a deep shape regression network. Face frontalization is achieved by utilizing piecewise affine transformations. For the final analysis, we present an emotion recognition system that utilizes HOG features and a random forest classifier and a respiratory rate analysis module that computes average temperatures from an automatically detected region of interest. Results show that our combined system achieves a performance which is comparable to current stand-alone state-of-the-art methods for thermal face and landmark datection and a classification accuracy of 65.75% for four basic emotions. MDPI 2019-09-24 /pmc/articles/PMC6806182/ /pubmed/31554260 http://dx.doi.org/10.3390/s19194135 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kopaczka, Marcin
Breuer, Lukas
Schock, Justus
Merhof, Dorit
A Modular System for Detection, Tracking and Analysis of Human Faces in Thermal Infrared Recordings †
title A Modular System for Detection, Tracking and Analysis of Human Faces in Thermal Infrared Recordings †
title_full A Modular System for Detection, Tracking and Analysis of Human Faces in Thermal Infrared Recordings †
title_fullStr A Modular System for Detection, Tracking and Analysis of Human Faces in Thermal Infrared Recordings †
title_full_unstemmed A Modular System for Detection, Tracking and Analysis of Human Faces in Thermal Infrared Recordings †
title_short A Modular System for Detection, Tracking and Analysis of Human Faces in Thermal Infrared Recordings †
title_sort modular system for detection, tracking and analysis of human faces in thermal infrared recordings †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6806182/
https://www.ncbi.nlm.nih.gov/pubmed/31554260
http://dx.doi.org/10.3390/s19194135
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