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So Tashiro

dblp:247/4034 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2019
—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 first-authorHuman-computer interaction and ubiquitous computing · 1 · 1 first-author

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
Interaction techniques and input · 100%
Artificial intelligence
1 paper
Robot navigation and mapping · 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
Interaction techniques and input › spatial interaction › 3d interaction
3d positioning
0.412019
3D Positioning System Based on One-handed Thumb Interactions for 3D Annotation Placement · VR 2019
Robotics › Robot navigation and mapping
SLAM
0.112019
3D Positioning System Based on One-handed Thumb Interactions for 3D Annotation Placement · VR 2019
Virtual and augmented reality › augmented reality › augmented reality visualization
augmented reality annotation
0.112019
3D Positioning System Based on One-handed Thumb Interactions for 3D Annotation Placement · VR 2019

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

robust estimator · 0.8robust estimators · 0.4
YearPublicationVenuePosition
2019 3D Positioning System Based on One-handed Thumb Interactions for 3D Annotation Placement
abstract
This paper presents a 3D positioning system based on one-handed thumb interactions for simple 3D annotation placement with a smart-phone. To place an annotation at a target point in the real environment, the 3D coordinate of the point is computed by interactively selecting the corresponding points in multiple views by users while performing SLAM. Generally, it is difficult for users to precisely select an intended pixel on the touchscreen. Therefore, we propose to compute the 3D coordinate from multiple observations with a robust estimator to have the tolerance to the inaccurate user inputs. In addition, we developed three pixel selection methods based on one-handed thumb interactions. A pixel is selected at the thumb position at a live view in FingAR, the position of a reticle marker at a live view in SnipAR, or that of a movable reticle marker at a freezed view in FreezAR. In the preliminary evaluation, we investigated the 3D positioning accuracy of each method.
So Tashiro, Hideaki Uchiyama, Diego Thomas, Rin-Ichiro Taniguchi
VR1