Low cost gaze estimation: knowledge-based solutions

Eye tracking technology in low resolution scenarios is not a completely solved issue to date. The possibility of using eye tracking in a mobile gadget is a challenging objective that would permit to spread this technology to non-explored fields. In this paper, a knowledge based approach is presented...

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Autores: Martinikorena Aranburu, Ion, Larumbe Bergera, Andoni, Ariz Galilea, Mikel, Porta Cuéllar, Sonia, Cabeza Laguna, Rafael, Villanueva Larre, Arantxa
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2020
País:España
Institución:Universidad Pública de Navarra
Repositorio:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
OAI Identifier:oai:academica-e.unavarra.es:2454/36191
Acceso en línea:https://hdl.handle.net/2454/36191
Access Level:acceso abierto
Palabra clave:Gaze estimation methods
Low resolution
Eye tracking
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spelling Low cost gaze estimation: knowledge-based solutionsMartinikorena Aranburu, IonLarumbe Bergera, AndoniAriz Galilea, MikelPorta Cuéllar, SoniaCabeza Laguna, RafaelVillanueva Larre, ArantxaGaze estimation methodsLow resolutionEye trackingEye tracking technology in low resolution scenarios is not a completely solved issue to date. The possibility of using eye tracking in a mobile gadget is a challenging objective that would permit to spread this technology to non-explored fields. In this paper, a knowledge based approach is presented to solve gaze estimation in low resolution settings. The understanding of the high resolution paradigm permits to propose alternative models to solve gaze estimation. In this manner, three models are presented: a geometrical model, an interpolation model and a compound model, as solutions for gaze estimation for remote low resolution systems. Since this work considers head position essential to improve gaze accuracy, a method for head pose estimation is also proposed. The methods are validated in an optimal framework, I2Head database, which combines head and gaze data. The experimental validation of the models demonstrates their sensitivity to image processing inaccuracies, critical in the case of the geometrical model. Static and extreme movement scenarios are analyzed showing the higher robustness of compound and geometrical models in the presence of user’s displacement. Accuracy values of about 3◦ have been obtained, increasing to values close to 5◦ in extreme displacement settings, results fully comparable with the state-of-the-art.This work was supported in part by the Ministry of Economy and Competitiveness under Grant TIN2014-52897-R and in part by the Ministry of Science, Innovation and Universities under Grant TIN2017-84388-R.IEEEIngeniería Eléctrica, Electrónica y de ComunicaciónIngeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren2020info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfhttps://hdl.handle.net/2454/36191reponame:Academica-e. Repositorio Institucional de la Universidad Pública de Navarrainstname:Universidad Pública de NavarraInglésinfo:eu-repo/grantAgreement/MINECO//TIN2014-52897-Rinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-84388-R© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work.info:eu-repo/semantics/openAccessoai:academica-e.unavarra.es:2454/361912026-06-17T12:41:47Z
dc.title.none.fl_str_mv Low cost gaze estimation: knowledge-based solutions
title Low cost gaze estimation: knowledge-based solutions
spellingShingle Low cost gaze estimation: knowledge-based solutions
Martinikorena Aranburu, Ion
Gaze estimation methods
Low resolution
Eye tracking
title_short Low cost gaze estimation: knowledge-based solutions
title_full Low cost gaze estimation: knowledge-based solutions
title_fullStr Low cost gaze estimation: knowledge-based solutions
title_full_unstemmed Low cost gaze estimation: knowledge-based solutions
title_sort Low cost gaze estimation: knowledge-based solutions
dc.creator.none.fl_str_mv Martinikorena Aranburu, Ion
Larumbe Bergera, Andoni
Ariz Galilea, Mikel
Porta Cuéllar, Sonia
Cabeza Laguna, Rafael
Villanueva Larre, Arantxa
author Martinikorena Aranburu, Ion
author_facet Martinikorena Aranburu, Ion
Larumbe Bergera, Andoni
Ariz Galilea, Mikel
Porta Cuéllar, Sonia
Cabeza Laguna, Rafael
Villanueva Larre, Arantxa
author_role author
author2 Larumbe Bergera, Andoni
Ariz Galilea, Mikel
Porta Cuéllar, Sonia
Cabeza Laguna, Rafael
Villanueva Larre, Arantxa
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Ingeniería Eléctrica, Electrónica y de Comunicación
Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren
dc.subject.none.fl_str_mv Gaze estimation methods
Low resolution
Eye tracking
topic Gaze estimation methods
Low resolution
Eye tracking
description Eye tracking technology in low resolution scenarios is not a completely solved issue to date. The possibility of using eye tracking in a mobile gadget is a challenging objective that would permit to spread this technology to non-explored fields. In this paper, a knowledge based approach is presented to solve gaze estimation in low resolution settings. The understanding of the high resolution paradigm permits to propose alternative models to solve gaze estimation. In this manner, three models are presented: a geometrical model, an interpolation model and a compound model, as solutions for gaze estimation for remote low resolution systems. Since this work considers head position essential to improve gaze accuracy, a method for head pose estimation is also proposed. The methods are validated in an optimal framework, I2Head database, which combines head and gaze data. The experimental validation of the models demonstrates their sensitivity to image processing inaccuracies, critical in the case of the geometrical model. Static and extreme movement scenarios are analyzed showing the higher robustness of compound and geometrical models in the presence of user’s displacement. Accuracy values of about 3◦ have been obtained, increasing to values close to 5◦ in extreme displacement settings, results fully comparable with the state-of-the-art.
publishDate 2020
dc.date.none.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2454/36191
url https://hdl.handle.net/2454/36191
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv info:eu-repo/grantAgreement/MINECO//TIN2014-52897-R
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-84388-R
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
dc.source.none.fl_str_mv reponame:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
instname:Universidad Pública de Navarra
instname_str Universidad Pública de Navarra
reponame_str Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
collection Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
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