Beyond basic tuning: exploring discrepancies in user and setup calibration for gaze estimation

dc.contributor.authorGarde Lecumberri, Gonzalo
dc.contributor.authorArmendáriz Armenteros, José María
dc.contributor.authorBeruete Cerezo, Rubén
dc.contributor.authorCabeza Laguna, Rafael
dc.contributor.authorVillanueva Larre, Arantxa
dc.contributor.departmentIngeniería Eléctrica, Electrónica y de Comunicaciónes_ES
dc.contributor.departmentIngeniaritza Elektrikoa, Elektronikoa eta Telekomunikazio Ingeniaritzaeu
dc.date.accessioned2024-12-12T09:50:57Z
dc.date.available2024-12-12T09:50:57Z
dc.date.issued2024-06-04
dc.date.updated2024-12-12T09:43:08Z
dc.description.abstractCalibrating gaze estimation models is crucial to maximize the effectiveness of these systems, although its implementation also poses challenges related to usability. Therefore, the simplification of this process is key. In this work, we dissect the impact of calibration due to both the environment and the user in gaze estimation models that employ general-purpose devices. We aim to replicate a workflow close to the final application by starting with pre-trained models and subsequently calibrating them using different strategies, testing under various camera arrangements and user-specific variability. The results indicate differentiation between the impact due to the user and the setup, being the components due to the users a slightly more pronounced impact than those related to the setup, opening the door to understanding calibration as a composite process. In any case, the development of calibration-free remote gaze estimation solutions remains a great challenge, given the crucial role of calibration.en
dc.format.mimetypeapplication/pdfen
dc.identifier.citationGarde, G., Armendariz, J. M., Cerezo, R. B., Cabeza, R., Villanueva, A. (2024) Beyond basic tuning: exploring discrepancies in user and setup calibration for gaze estimation. In Mohamed Khamis and Yusuke Sugano (Eds.), ETRA '24: Proceedings of the 2024 Symposium on Eye Tracking Research and Applications (pp. 1-8). Association for Computing Machinery. https://doi.org/10.1145/3649902.3653346
dc.identifier.doi10.1145/3649902.3653346
dc.identifier.isbn979-8-4007-0607-3
dc.identifier.urihttps://academica-e.unavarra.es/handle/2454/52705
dc.language.isoeng
dc.publisherACM
dc.relation.ispartofIn Khamis, M.; Sugano, Y. (Eds.). ETRA '24: Proceedings of the 2024 Symposium on Eye Tracking Research and Applications. Association for Computing Machinery; 2024. p. 1-8
dc.relation.publisherversionhttps://doi.org/10.1145/3649902.3653346
dc.rights© 2024 Copyright held by the owner/author(s). This work is licensed under a Creative Commons Attribution International 4.0 License.
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCalibration algorithmsen
dc.subjectComputer visionen
dc.subjectGaze estimationen
dc.subjectLow-cost and smartphone systemsen
dc.titleBeyond basic tuning: exploring discrepancies in user and setup calibration for gaze estimationen
dc.typeinfo:eu-repo/semantics/conferenceObject
dc.type.versioninfo:eu-repo/semantics/publishedVersion
dspace.entity.typePublication
relation.isAuthorOfPublicatione764f502-1d84-436f-81cd-97bfbe0240f4
relation.isAuthorOfPublication42fe20f8-5341-4c0e-8686-333ce816adfd
relation.isAuthorOfPublicationd3bfd5bf-8426-455b-bcc4-897ddb0d4c2e
relation.isAuthorOfPublication.latestForDiscoverye764f502-1d84-436f-81cd-97bfbe0240f4

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