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Hong-Song Toh

dblp:95/9583 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2011
—ORCID · none

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

Human-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 networks
1 paper
Wireless sensing and localization · 100%
Human-computer interaction and pervasive computing
1 paper
Ubiquitous computing and smart environments · 77% Wearable and physiological sensing · 23%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Ubiquitous computing and smart environments
mobile sensing
0.112011
A robust dead-reckoning pedestrian tracking system with low cost sensors · PerCom 2011
Wireless sensing and localization › navigation
dead reckoning
0.112011
A robust dead-reckoning pedestrian tracking system with low cost sensors · PerCom 2011
Wireless sensing and localization › tracking › indoor tracking
indoor pedestrian tracking
0.112011
A robust dead-reckoning pedestrian tracking system with low cost sensors · PerCom 2011
Wearable and physiological sensing
inertial sensing
0.012011
A robust dead-reckoning pedestrian tracking system with low cost sensors · PerCom 2011

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

sensor fusion · 0.2maximum a posteriori estimation · 0.2
YearPublicationVenuePosition
2011 A robust dead-reckoning pedestrian tracking system with low cost sensors
abstract
The emergence of personal mobile device with low cost sensors, such as accelerometer and digital compass, has made dead-reckoning (DR) an attractive choice for indoor pedestrian tracking. In this paper, we propose a robust DR pedestrian tracking system on top of such commercially accessible sensor sets capable of DR. The proposed method exploits the fact that, multiple DR systems, carried by the same pedestrian, have stable relative displacements with respect to the center of motion, and therefore to each other. We first formulate the robust tracking task as a generalized maximum a posteriori sensor fusion problem, and then we narrow it to a simple computation procedure with certain assumptions. A prototype is implemented and evaluated with a benchmark system that collects ground truth efficiently and accurately. In a practical indoor testbed, the proposed scheme has exhibited robust tracking performance, with reduction in average tracking error up to 73.7%, compared to traditional DR tracking methods.
Yunye Jin, Hong-Song Toh, Wee-Seng Soh, Lawrence Wai-Choong Wong
PerCom2