Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Momoko Maezawa

dblp:194/5430 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

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

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

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.

Computer graphics and multimedia
1 paper
Virtual and augmented reality · 100%
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
Virtual and augmented reality › mixed reality
diminished reality
0.312017
Diminished hand: A diminished reality-based work area visualization · VR 2017

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

multi-camera capture · 0.6light field rendering · 0.6
YearPublicationVenuePosition
2017 Diminished hand: A diminished reality-based work area visualization
abstract
Live instructors perspective videos are useful to present intuitive visual instructions for trainees in medical and industrial settings. In such videos, the instructors hands often hide the work area. In this demo, we present a diminished hand for visualizing the work area hidden by hands by capturing the work area with multiple cameras. To achieve the diminished reality, we use a light field rendering technique, in which light rays avoid passing through penalty points set in the unstructured light fields reconstructed from the multiple viewpoint images.
Shohei Mori, Momoko Maezawa, Naoto Ienaga, Hideo Saito 0001
VR2