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Kenya Sakamoto

dblp:265/2867 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Wearable and physiological sensing · 100%
Computer graphics and multimedia
1 paper
Virtual and augmented reality · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wearable and physiological sensing › eye tracking
gaze-based interaction
0.812024
EyeShadows: Peripheral Virtual Copies for Rapid Gaze Selection and Interaction · VR 2024
Wearable and physiological sensing › eye tracking › gaze-based interaction
gaze-based selection
0.812024
EyeShadows: Peripheral Virtual Copies for Rapid Gaze Selection and Interaction · VR 2024
Virtual and augmented reality
augmented reality
0.212024
EyeShadows: Peripheral Virtual Copies for Rapid Gaze Selection and Interaction · VR 2024

Methods — techniques the papers use, named apart from their topics

user study · 1.5performance evaluation · 1.5
YearPublicationVenuePosition
2024 EyeShadows: Peripheral Virtual Copies for Rapid Gaze Selection and Interaction
abstract
In eye-tracked augmented and virtual reality (AR/VR), instantaneous and accurate hands-free selection of virtual elements is still a significant challenge. Though other methods that involve gaze-coupled head movements or hovering can improve selection times in comparison to methods like gaze-dwell, they are either not instantaneous or have difficulty ensuring that the user’s selection is deliberate. In this paper, we present EyeShadows, an eye gaze-based selection system that takes advantage of peripheral copies (shadows) of items that allow for quick selection and manipulation of an object or corresponding menus. This method is compatible with a variety of different selection tasks and controllable items, avoids the Midas touch problem, does not clutter the virtual environment, and is context sensitive. We have implemented and refined this selection tool for VR and AR, including testing with optical and video see-through (OST/VST) displays. Moreover, we demonstrate that this method can be used for a wide range of AR and VR applications, including manipulation of sliders or analog elements. We test its performance in VR against three other selection techniques, including dwell (baseline), an inertial reticle, and head-coupled selection. Results showed that selection with EyeShadows was significantly faster than dwell (baseline), outperforming in the select and search and select tasks by 29.8% and 15.7%, respectively, though error rates varied between tasks.
Jason Orlosky, Chang Liu 0081, Kenya Sakamoto, Ludwig Sidenmark, Adam Mansour
VR3