Brittany Dao

dblp:134/5897 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2013
—ORCID · unresolved

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.

Computer graphics and multimedia
1 paper
Virtual and augmented reality · 50% Visualization and visual analytics · 50%
Human-computer interaction and pervasive computing
1 paper
Usability and user experience research · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Virtual and augmented reality › augmented reality
mobile augmented reality
0.212013
Early steps towards understanding text legibility in handheld augmented reality · VR 2013
Visualization and visual analytics › perception
text legibility
0.212013
Early steps towards understanding text legibility in handheld augmented reality · VR 2013

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

literature survey · 0.3
YearPublicationVenuePosition
2013 Early steps towards understanding text legibility in handheld augmented reality
abstract
Over the past decades, augmented reality (AR) has seen vast improvements in graphic displays and mobile tracking capabilities. To our knowledge, handheld AR researcher in text legibility has mostly focused on algorithms for overlaying screen-aligned annotations; no one has yet employed a series of user-based studies to systematically investigate text legibility in handheld AR applications. In this preliminary work, we survey current approaches to text depictions in AR applications and the literature. We have found no single consistent form of displaying text, but see some basic trends emerging. This initial work lays the foundation for examining different text styles in various environments in order to create guidelines for effective text drawing approaches. By assessing current strategies for rendering text labels in handheld AR, we can catalog drawing styles for use in follow-on user-based studies.
Brittany Dao, Joseph L. Gabbard
VR1