BimodalGaze: Seamlessly Refined Pointing with Gaze and Filtered Gestural Head Movement. Sidenmark, L., Mardanbegi, D., Gomez, A. R., Clarke, C., & Gellersen, H. In ACM Symposium on Eye Tracking Research and Applications, of ETRA '20 Full Papers, New York, NY, USA, 2020. Association for Computing Machinery.
Paper doi abstract bibtex 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.
@inproceedings{10.1145/3379155.3391312,
author = {Sidenmark, Ludwig and Mardanbegi, Diako and Gomez, Argenis Ramirez and Clarke, Christopher and Gellersen, Hans},
title = {BimodalGaze: Seamlessly Refined Pointing with Gaze and Filtered Gestural Head Movement},
year = {2020},
isbn = {9781450371339},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3379155.3391312},
doi = {10.1145/3379155.3391312},
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. },
booktitle = {ACM Symposium on Eye Tracking Research and Applications},
articleno = {8},
numpages = {9},
keywords = {Gaze interaction, Eye tracking, Refinement, Virtual reality, Eye-head coordination},
location = {Stuttgart, Germany},
series = {ETRA '20 Full Papers}
}
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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. 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