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Visual and Thermal Image Processing for Facial Specific Landmark Detection to Infer Emotions in a Child-Robot Interaction

Child-Robot Interaction (CRI) has become increasingly addressed in research and applications. This work proposes a system for emotion recognition in children, recording facial images by both visual (RGB—red, green and blue) and Infrared Thermal Imaging (IRTI) cameras. For this purpose, the Viola-Jon...

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Autores principales: Goulart, Christiane, Valadão, Carlos, Delisle-Rodriguez, Denis, Funayama, Douglas, Favarato, Alvaro, Baldo, Guilherme, Binotte, Vinícius, Caldeira, Eliete, Bastos-Filho, Teodiano
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6650968/
https://www.ncbi.nlm.nih.gov/pubmed/31248004
http://dx.doi.org/10.3390/s19132844
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author Goulart, Christiane
Valadão, Carlos
Delisle-Rodriguez, Denis
Funayama, Douglas
Favarato, Alvaro
Baldo, Guilherme
Binotte, Vinícius
Caldeira, Eliete
Bastos-Filho, Teodiano
author_facet Goulart, Christiane
Valadão, Carlos
Delisle-Rodriguez, Denis
Funayama, Douglas
Favarato, Alvaro
Baldo, Guilherme
Binotte, Vinícius
Caldeira, Eliete
Bastos-Filho, Teodiano
author_sort Goulart, Christiane
collection PubMed
description Child-Robot Interaction (CRI) has become increasingly addressed in research and applications. This work proposes a system for emotion recognition in children, recording facial images by both visual (RGB—red, green and blue) and Infrared Thermal Imaging (IRTI) cameras. For this purpose, the Viola-Jones algorithm is used on color images to detect facial regions of interest (ROIs), which are transferred to the thermal camera plane by multiplying a homography matrix obtained through the calibration process of the camera system. As a novelty, we propose to compute the error probability for each ROI located over thermal images, using a reference frame manually marked by a trained expert, in order to choose that ROI better placed according to the expert criteria. Then, this selected ROI is used to relocate the other ROIs, increasing the concordance with respect to the reference manual annotations. Afterwards, other methods for feature extraction, dimensionality reduction through Principal Component Analysis (PCA) and pattern classification by Linear Discriminant Analysis (LDA) are applied to infer emotions. The results show that our approach for ROI locations may track facial landmarks with significant low errors with respect to the traditional Viola-Jones algorithm. These ROIs have shown to be relevant for recognition of five emotions, specifically disgust, fear, happiness, sadness, and surprise, with our recognition system based on PCA and LDA achieving mean accuracy (ACC) and Kappa values of 85.75% and 81.84%, respectively. As a second stage, the proposed recognition system was trained with a dataset of thermal images, collected on 28 typically developing children, in order to infer one of five basic emotions (disgust, fear, happiness, sadness, and surprise) during a child-robot interaction. The results show that our system can be integrated to a social robot to infer child emotions during a child-robot interaction.
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spelling pubmed-66509682019-08-07 Visual and Thermal Image Processing for Facial Specific Landmark Detection to Infer Emotions in a Child-Robot Interaction Goulart, Christiane Valadão, Carlos Delisle-Rodriguez, Denis Funayama, Douglas Favarato, Alvaro Baldo, Guilherme Binotte, Vinícius Caldeira, Eliete Bastos-Filho, Teodiano Sensors (Basel) Article Child-Robot Interaction (CRI) has become increasingly addressed in research and applications. This work proposes a system for emotion recognition in children, recording facial images by both visual (RGB—red, green and blue) and Infrared Thermal Imaging (IRTI) cameras. For this purpose, the Viola-Jones algorithm is used on color images to detect facial regions of interest (ROIs), which are transferred to the thermal camera plane by multiplying a homography matrix obtained through the calibration process of the camera system. As a novelty, we propose to compute the error probability for each ROI located over thermal images, using a reference frame manually marked by a trained expert, in order to choose that ROI better placed according to the expert criteria. Then, this selected ROI is used to relocate the other ROIs, increasing the concordance with respect to the reference manual annotations. Afterwards, other methods for feature extraction, dimensionality reduction through Principal Component Analysis (PCA) and pattern classification by Linear Discriminant Analysis (LDA) are applied to infer emotions. The results show that our approach for ROI locations may track facial landmarks with significant low errors with respect to the traditional Viola-Jones algorithm. These ROIs have shown to be relevant for recognition of five emotions, specifically disgust, fear, happiness, sadness, and surprise, with our recognition system based on PCA and LDA achieving mean accuracy (ACC) and Kappa values of 85.75% and 81.84%, respectively. As a second stage, the proposed recognition system was trained with a dataset of thermal images, collected on 28 typically developing children, in order to infer one of five basic emotions (disgust, fear, happiness, sadness, and surprise) during a child-robot interaction. The results show that our system can be integrated to a social robot to infer child emotions during a child-robot interaction. MDPI 2019-06-26 /pmc/articles/PMC6650968/ /pubmed/31248004 http://dx.doi.org/10.3390/s19132844 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
Goulart, Christiane
Valadão, Carlos
Delisle-Rodriguez, Denis
Funayama, Douglas
Favarato, Alvaro
Baldo, Guilherme
Binotte, Vinícius
Caldeira, Eliete
Bastos-Filho, Teodiano
Visual and Thermal Image Processing for Facial Specific Landmark Detection to Infer Emotions in a Child-Robot Interaction
title Visual and Thermal Image Processing for Facial Specific Landmark Detection to Infer Emotions in a Child-Robot Interaction
title_full Visual and Thermal Image Processing for Facial Specific Landmark Detection to Infer Emotions in a Child-Robot Interaction
title_fullStr Visual and Thermal Image Processing for Facial Specific Landmark Detection to Infer Emotions in a Child-Robot Interaction
title_full_unstemmed Visual and Thermal Image Processing for Facial Specific Landmark Detection to Infer Emotions in a Child-Robot Interaction
title_short Visual and Thermal Image Processing for Facial Specific Landmark Detection to Infer Emotions in a Child-Robot Interaction
title_sort visual and thermal image processing for facial specific landmark detection to infer emotions in a child-robot interaction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6650968/
https://www.ncbi.nlm.nih.gov/pubmed/31248004
http://dx.doi.org/10.3390/s19132844
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