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Gaoshuai Cao

dblp:272/5390 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2020
—ORCID · none

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

Computer networks · 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 networks
1 paper
Wireless sensing and localization · 100%
Human-computer interaction and pervasive computing
1 paper
Wearable and physiological sensing · 100%

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

TopicWeightPapersLastEvidence papers
Wireless sensing and localization › tracking › motion tracking
acoustic motion tracking
0.412020
EarphoneTrack: involving earphones into the ecosystem of acoustic motion tracking · SenSys 2020
Wearable and physiological sensing
earable sensing
0.112020
EarphoneTrack: involving earphones into the ecosystem of acoustic motion tracking · SenSys 2020

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

acoustic signal processing · 0.9
YearPublicationVenuePosition
2020 EarphoneTrack: involving earphones into the ecosystem of acoustic motion tracking
abstract
Acoustic motion tracking is an exciting new research area with promising progress in the last few years. Due to the inherent low propagation speed in the air, acoustic signals have the unique advantage of fine sensing granularity compared to RF signals. Speakers and microphones nowadays are pervasively available in devices surrounding us, such as smartphones and voice-controlled smart speakers. Though promising, one fundamental issue hindering the adoption of acoustic-based motion tracking is that the positions of microphones and speakers inside a device are fixed, which greatly limits the flexibility of acoustic motion tracking. In this work, we propose a new modality of acoustic motion tracking using earphones. Earphone-based tracking mitigates the constraints associated with traditional smartphone-based tracking. With novel designs and comprehensive experiments, we show earphone-based motion tracking can achieve a great flexibility and a high accuracy at the same time. We believe this is an important step towards "earable" sensing.
Gaoshuai Cao, Kuang Yuan, Jie Xiong 0001, Panlong Yang, Yubo Yan, Hao Zhou 0001, Xiang-Yang Li 0001
SenSys1