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Towards Mitigating the Eye Gaze Tracking Uncertainty in Virtual Reality. / Ryabinin, Konstantin ; Chuprina, Svetlana .

Computational Science - ICCS 2022, 22nd International Conference, Proceedings: 22nd International Conference, London, UK, June 21–23, 2022, Proceedings, Part IV. ред. / Derek Groen; Clélia de Mulatier; Valeria V. Krzhizhanovskaya; Peter M.A. Sloot; Maciej Paszynski; Jack J. Dongarra. Cham : Springer Nature, 2022. стр. 623-636 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 13353 LNCS).

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Harvard

Ryabinin, K & Chuprina, S 2022, Towards Mitigating the Eye Gaze Tracking Uncertainty in Virtual Reality. в D Groen, C de Mulatier, VV Krzhizhanovskaya, PMA Sloot, M Paszynski & JJ Dongarra (ред.), Computational Science - ICCS 2022, 22nd International Conference, Proceedings: 22nd International Conference, London, UK, June 21–23, 2022, Proceedings, Part IV. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Том. 13353 LNCS, Springer Nature, Cham, стр. 623-636, Computational Science – ICCS 2022, London, Великобритания, 21/06/22. https://doi.org/10.1007/978-3-031-08760-8_51

APA

Ryabinin, K., & Chuprina, S. (2022). Towards Mitigating the Eye Gaze Tracking Uncertainty in Virtual Reality. в D. Groen, C. de Mulatier, V. V. Krzhizhanovskaya, P. M. A. Sloot, M. Paszynski, & J. J. Dongarra (Ред.), Computational Science - ICCS 2022, 22nd International Conference, Proceedings: 22nd International Conference, London, UK, June 21–23, 2022, Proceedings, Part IV (стр. 623-636). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Том 13353 LNCS). Springer Nature. https://doi.org/10.1007/978-3-031-08760-8_51

Vancouver

Ryabinin K, Chuprina S. Towards Mitigating the Eye Gaze Tracking Uncertainty in Virtual Reality. в Groen D, de Mulatier C, Krzhizhanovskaya VV, Sloot PMA, Paszynski M, Dongarra JJ, Редакторы, Computational Science - ICCS 2022, 22nd International Conference, Proceedings: 22nd International Conference, London, UK, June 21–23, 2022, Proceedings, Part IV. Cham: Springer Nature. 2022. стр. 623-636. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-031-08760-8_51

Author

Ryabinin, Konstantin ; Chuprina, Svetlana . / Towards Mitigating the Eye Gaze Tracking Uncertainty in Virtual Reality. Computational Science - ICCS 2022, 22nd International Conference, Proceedings: 22nd International Conference, London, UK, June 21–23, 2022, Proceedings, Part IV. Редактор / Derek Groen ; Clélia de Mulatier ; Valeria V. Krzhizhanovskaya ; Peter M.A. Sloot ; Maciej Paszynski ; Jack J. Dongarra. Cham : Springer Nature, 2022. стр. 623-636 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

BibTeX

@inproceedings{4a498b178cb948c48e1bbfbff556786b,
title = "Towards Mitigating the Eye Gaze Tracking Uncertainty in Virtual Reality",
abstract = "We propose a novel algorithm to evaluate and mitigate the uncertainty of data reported by eye gaze tracking devices embedded in virtual reality head-mounted displays. Our algorithm first is calibrated by leveraging unit quaternions to encode angular differences between reported and ground-truth gaze directions, then interpolates these quaternions for each gaze sample, and finally corrects gaze directions by rotating them using interpolated quaternions. The real part of the interpolated quaternion is used as the certainty factor for the corresponding gaze direction sample. The proposed algorithm is implemented in the VRSciVi Workbench within the ontology-driven SciVi visual analytics platform and can be used to improve the eye gaze tracking quality in different virtual reality applications including the ones for Digital Humanities research. The tests of the proposed algorithm revealed its capability of increasing eye tracking accuracy by 25% and precision by 32% compared with the raw output of the Tobii tracker embedded in the Vive Pro Eye head-mounted display. In addition, the certainty factors calculated help to acknowledge the quality of reported gaze directions in the subsequent data analysis stages. Due to the ontology-driven software generation, the proposed approach enables high-level adaptation to the specifics of the experiments in virtual reality.Keywords",
keywords = "Eye tracking, Ontology-driven software generation, Quaternion-based model, Uncertainty mitigation, Virtual reality",
author = "Konstantin Ryabinin and Svetlana Chuprina",
note = "Ryabinin, K., Chuprina, S. (2022). Towards Mitigating the Eye Gaze Tracking Uncertainty in Virtual Reality. In: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13353. Springer, Cham. https://doi.org/10.1007/978-3-031-08760-8_51 Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.; Computational Science – ICCS 2022 : 22nd International Conference ; Conference date: 21-06-2022 Through 23-06-2022",
year = "2022",
doi = "10.1007/978-3-031-08760-8_51",
language = "English",
isbn = "978-3-031-08759-2",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "623--636",
editor = "Derek Groen and {de Mulatier}, Cl{\'e}lia and Krzhizhanovskaya, {Valeria V.} and Sloot, {Peter M.A.} and Maciej Paszynski and Dongarra, {Jack J.}",
booktitle = "Computational Science - ICCS 2022, 22nd International Conference, Proceedings",
address = "Germany",

}

RIS

TY - GEN

T1 - Towards Mitigating the Eye Gaze Tracking Uncertainty in Virtual Reality

AU - Ryabinin, Konstantin

AU - Chuprina, Svetlana

N1 - Ryabinin, K., Chuprina, S. (2022). Towards Mitigating the Eye Gaze Tracking Uncertainty in Virtual Reality. In: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13353. Springer, Cham. https://doi.org/10.1007/978-3-031-08760-8_51 Publisher Copyright: © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

PY - 2022

Y1 - 2022

N2 - We propose a novel algorithm to evaluate and mitigate the uncertainty of data reported by eye gaze tracking devices embedded in virtual reality head-mounted displays. Our algorithm first is calibrated by leveraging unit quaternions to encode angular differences between reported and ground-truth gaze directions, then interpolates these quaternions for each gaze sample, and finally corrects gaze directions by rotating them using interpolated quaternions. The real part of the interpolated quaternion is used as the certainty factor for the corresponding gaze direction sample. The proposed algorithm is implemented in the VRSciVi Workbench within the ontology-driven SciVi visual analytics platform and can be used to improve the eye gaze tracking quality in different virtual reality applications including the ones for Digital Humanities research. The tests of the proposed algorithm revealed its capability of increasing eye tracking accuracy by 25% and precision by 32% compared with the raw output of the Tobii tracker embedded in the Vive Pro Eye head-mounted display. In addition, the certainty factors calculated help to acknowledge the quality of reported gaze directions in the subsequent data analysis stages. Due to the ontology-driven software generation, the proposed approach enables high-level adaptation to the specifics of the experiments in virtual reality.Keywords

AB - We propose a novel algorithm to evaluate and mitigate the uncertainty of data reported by eye gaze tracking devices embedded in virtual reality head-mounted displays. Our algorithm first is calibrated by leveraging unit quaternions to encode angular differences between reported and ground-truth gaze directions, then interpolates these quaternions for each gaze sample, and finally corrects gaze directions by rotating them using interpolated quaternions. The real part of the interpolated quaternion is used as the certainty factor for the corresponding gaze direction sample. The proposed algorithm is implemented in the VRSciVi Workbench within the ontology-driven SciVi visual analytics platform and can be used to improve the eye gaze tracking quality in different virtual reality applications including the ones for Digital Humanities research. The tests of the proposed algorithm revealed its capability of increasing eye tracking accuracy by 25% and precision by 32% compared with the raw output of the Tobii tracker embedded in the Vive Pro Eye head-mounted display. In addition, the certainty factors calculated help to acknowledge the quality of reported gaze directions in the subsequent data analysis stages. Due to the ontology-driven software generation, the proposed approach enables high-level adaptation to the specifics of the experiments in virtual reality.Keywords

KW - Eye tracking

KW - Ontology-driven software generation

KW - Quaternion-based model

KW - Uncertainty mitigation

KW - Virtual reality

UR - http://www.scopus.com/inward/record.url?scp=85134336895&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/1b9a9159-5e95-3b7e-997d-f02554bdf63b/

U2 - 10.1007/978-3-031-08760-8_51

DO - 10.1007/978-3-031-08760-8_51

M3 - Conference contribution

SN - 978-3-031-08759-2

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 623

EP - 636

BT - Computational Science - ICCS 2022, 22nd International Conference, Proceedings

A2 - Groen, Derek

A2 - de Mulatier, Clélia

A2 - Krzhizhanovskaya, Valeria V.

A2 - Sloot, Peter M.A.

A2 - Paszynski, Maciej

A2 - Dongarra, Jack J.

PB - Springer Nature

CY - Cham

T2 - Computational Science – ICCS 2022

Y2 - 21 June 2022 through 23 June 2022

ER -

ID: 100626349