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  • Head_Gaze_pointing_ETRA20

    Rights statement: © ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ETRA '20 Full Papers: ACM Symposium on Eye Tracking Research and Applications, 2020 http://doi.acm.org/10.1145/3379155.3391312

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BimodalGaze: Seamlessly Refined Pointing with Gaze and Filtered Gestural Head Movement

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BimodalGaze : Seamlessly Refined Pointing with Gaze and Filtered Gestural Head Movement. / Sidenmark, Ludwig; Mardanbegi, Diako; Ramirez Gomez, Argenis; Clarke, Christopher; Gellersen, Hans.

Proceedings ETRA 2020 Full Papers - ACM Symposium on Eye Tracking Research and Applications. New York : ACM, 2020. 8.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paper

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@inproceedings{110b0cbcb5c44161a6acd7a4848a899a,
title = "BimodalGaze: Seamlessly Refined Pointing with Gaze and Filtered Gestural Head Movement",
abstract = "Eye gaze is a fast and ergonomic modality for pointing but limited in precision and accuracy. In this work, we introduce BimodalGaze, a novel technique for seamless head-based refinement of a gaze cursor. The technique leverages eye-head coordination insights to separate natural from gestural head movement. This allows users to quickly shift their gaze to targets over larger fields of view with naturally combined eye-head movement, and to refine the cursor position with gestural head movement. In contrast to an existing baseline, head refinement is invoked automatically, and only if a target is not already acquired by the initial gaze shift. Study results show that users reliably achieve fine-grained target selection, but we observed a higher rate of initial selection errors affecting overall performance. An in-depth analysis of user performance provides insight into the classification of natural versus gestural head movement, for improvement of BimodalGaze and other potential applications.",
keywords = "Eye tracking, Gaze interaction, Refinement, Eye-head coordination, Virtual reality",
author = "Ludwig Sidenmark and Diako Mardanbegi and {Ramirez Gomez}, Argenis and Christopher Clarke and Hans Gellersen",
note = "{\textcopyright} ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ETRA '20 Full Papers: ACM Symposium on Eye Tracking Research and Applications, 2020 http://doi.acm.org/10.1145/3379155.3391312",
year = "2020",
month = jun,
day = "2",
doi = "10.1145/3379155.3391312",
language = "English",
booktitle = "Proceedings ETRA 2020 Full Papers - ACM Symposium on Eye Tracking Research and Applications",
publisher = "ACM",

}

RIS

TY - GEN

T1 - BimodalGaze

T2 - Seamlessly Refined Pointing with Gaze and Filtered Gestural Head Movement

AU - Sidenmark, Ludwig

AU - Mardanbegi, Diako

AU - Ramirez Gomez, Argenis

AU - Clarke, Christopher

AU - Gellersen, Hans

N1 - © ACM, 2020. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in ETRA '20 Full Papers: ACM Symposium on Eye Tracking Research and Applications, 2020 http://doi.acm.org/10.1145/3379155.3391312

PY - 2020/6/2

Y1 - 2020/6/2

N2 - Eye gaze is a fast and ergonomic modality for pointing but limited in precision and accuracy. In this work, we introduce BimodalGaze, a novel technique for seamless head-based refinement of a gaze cursor. The technique leverages eye-head coordination insights to separate natural from gestural head movement. This allows users to quickly shift their gaze to targets over larger fields of view with naturally combined eye-head movement, and to refine the cursor position with gestural head movement. In contrast to an existing baseline, head refinement is invoked automatically, and only if a target is not already acquired by the initial gaze shift. Study results show that users reliably achieve fine-grained target selection, but we observed a higher rate of initial selection errors affecting overall performance. An in-depth analysis of user performance provides insight into the classification of natural versus gestural head movement, for improvement of BimodalGaze and other potential applications.

AB - Eye gaze is a fast and ergonomic modality for pointing but limited in precision and accuracy. In this work, we introduce BimodalGaze, a novel technique for seamless head-based refinement of a gaze cursor. The technique leverages eye-head coordination insights to separate natural from gestural head movement. This allows users to quickly shift their gaze to targets over larger fields of view with naturally combined eye-head movement, and to refine the cursor position with gestural head movement. In contrast to an existing baseline, head refinement is invoked automatically, and only if a target is not already acquired by the initial gaze shift. Study results show that users reliably achieve fine-grained target selection, but we observed a higher rate of initial selection errors affecting overall performance. An in-depth analysis of user performance provides insight into the classification of natural versus gestural head movement, for improvement of BimodalGaze and other potential applications.

KW - Eye tracking

KW - Gaze interaction

KW - Refinement

KW - Eye-head coordination

KW - Virtual reality

U2 - 10.1145/3379155.3391312

DO - 10.1145/3379155.3391312

M3 - Conference contribution/Paper

BT - Proceedings ETRA 2020 Full Papers - ACM Symposium on Eye Tracking Research and Applications

PB - ACM

CY - New York

ER -