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Josh Tabor

dblp:167/5966 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none

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

Computer networks · 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 networks
1 paper
Wireless sensing and localization · 100%
Human-computer interaction and pervasive computing
1 paper
Interaction techniques and input · 77% Ubiquitous computing and smart environments · 23%

Topics — the 3 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Interaction techniques and input
mobile interaction
0.212015
Extending Mobile Interaction Through Near-Field Visible Light Sensing · MobiCom 2015
Wireless sensing and localization › human sensing
finger localization
0.212015
Extending Mobile Interaction Through Near-Field Visible Light Sensing · MobiCom 2015
Wireless sensing and localization › optical sensing
visible light sensing
0.212015
Extending Mobile Interaction Through Near-Field Visible Light Sensing · MobiCom 2015

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

light propagation/reflection model · 0.4LED and light sensor · 0.4
YearPublicationVenuePosition
2015 Extending Mobile Interaction Through Near-Field Visible Light Sensing
abstract
Mobile devices are shrinking their form factors for portability, but user-mobile interaction is becoming increasingly challenging. In this paper, we propose a novel system called Okuli to meet this challenge. Okuli is a compact, low-cost system that can augment a mobile device and extend its interaction workspace to any nearby surface area. Okuli piggybacks on visible light communication modules, and uses a low-power LED and two light sensors to locate user's finger within the workspace. It is built on a light propagation/reflection model that achieves around one-centimeter location precision, with zero run-time training overhead. We have prototyped Okuli as an Android peripheral, with a 3D-printed shroud to host the LED and light sensors. Our experiments demonstrate Okuli's accuracy, stability, energy efficiency, as well as its potential in serving virtual keyboard and trackpad applications.
Chi Zhang 0018, Josh Tabor, Xinyu Zhang 0003
MobiCom2