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Hidetaka Katsuyama

dblp:335/5933 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0000-0001-6221-1303ORCID · reported

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

Human-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
Immersive interaction · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Immersive interaction › attention guidance
gaze guidance
0.812024
MOSion: Gaze Guidance with Motion-triggered Visual Cues by Mosaic Patterns · CHI 2024

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

user study · 0.8
YearPublicationVenuePosition
2024 MOSion: Gaze Guidance with Motion-triggered Visual Cues by Mosaic Patterns
abstract
We propose a gaze-guiding method called MOSion to adjust the guiding strength reacted to observers’ motion based on a high-speed projector and the afterimage effect in the human vision system. Our method decomposes the target area into mosaic patterns to embed visual cues in the perceived images. The patterns can only direct the attention of the moving observers to the target area. The stopping observer can see the original image with little distortion because of light integration in the visual perception. The precomputation of the patterns provides the adaptive guiding effect without tracking devices and computational costs depending on the movements. The evaluation and the user study show that the mosaic decomposition enhances the perceived saliency with a few visual artifacts, especially in moving conditions. Our method embedded in white lights works in various situations such as planar posters, advertisements, and curved objects.
Arisa Kohtani, Shio Miyafuji, Keishiro Uragaki, Hidetaka Katsuyama, Hideki Koike
CHI4