SeTA: semiautomatic tool for annotation of eye tracking images
| dc.contributor.author | Larumbe Bergera, Andoni | |
| dc.contributor.author | Porta Cuéllar, Sonia | |
| dc.contributor.author | Cabeza Laguna, Rafael | |
| dc.contributor.author | Villanueva Larre, Arantxa | |
| dc.contributor.department | Ingeniería Eléctrica, Electrónica y de Comunicación | es_ES |
| dc.contributor.department | Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren | eu |
| dc.date.accessioned | 2021-12-09T12:25:18Z | |
| dc.date.available | 2021-12-09T12:25:18Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | Availability of large scale tagged datasets is a must in the field of deep learning applied to the eye tracking challenge. In this paper, the potential of Supervised-Descent-Method (SDM) as a semiautomatic labelling tool for eye tracking images is shown. The objective of the paper is to evidence how the human effort needed for manually labelling large eye tracking datasets can be radically reduced by the use of cascaded regressors. Different applications are provided in the fields of high and low resolution systems. An iris/pupil center labelling is shown as example for low resolution images while a pupil contour points detection is demonstrated in high resolution. In both cases manual annotation requirements are drastically reduced. | en |
| dc.description.sponsorship | Spanish Ministry of Science, Innovation and Universities, contract TIN2017-84388-R | en |
| dc.format.extent | 5 p. | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.citation | Andoni Larumbe-Bergera, Sonia Porta, Rafael Cabeza, and Arantxa Villanueva. 2019. SeTA: Semiautomatic Tool for Annotation of Eye Tracking Images. In 2019 Symposium on Eye Tracking Research and Applications (ETRA ’19), June 25–28, 2019, Denver , CO, USA. ACM, New York, NY, USA, 5 pages.https://doi.org/10.1145/3314111.3319830 | en |
| dc.identifier.doi | 10.1145/3314111.3319830 | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/41214 | |
| dc.language.iso | eng | en |
| dc.publisher | ACM | en |
| dc.relation.ispartof | ETRA '19: Proceedings of the 11th ACM Symposium on Eye Tracking Research & Applications, June 2019, Article No. 45, Pages 1–5 | en |
| dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-84388-R/ES/ | |
| dc.relation.publisherversion | https://doi.org/10.1145/3314111.3319830 | |
| dc.rights | © 2019 Copyright held by the owner/author(s). | en |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.subject | Image annotation | en |
| dc.subject | Eye tracking | en |
| dc.subject | Supervised-descent method | en |
| dc.title | SeTA: semiautomatic tool for annotation of eye tracking images | en |
| dc.type | info:eu-repo/semantics/conferenceObject | |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | |
| dspace.entity.type | Publication | |
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