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Rayana Boubezari

dblp:152/9649 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · unresolved

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
Internet of things and sensor networks · 77% Wireless sensing and localization · 23%

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

TopicWeightPapersLastEvidence papers
Internet of things and sensor networks › motion sensing › inertial sensing
orientation estimation
0.312017
LiCompass: Extracting orientation from polarized light · INFOCOM 2017
Wireless sensing and localization
indoor localization
0.112017
LiCompass: Extracting orientation from polarized light · INFOCOM 2017

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

trigonometric estimation · 0.3signal processing · 0.3
YearPublicationVenuePosition
2017 LiCompass: Extracting orientation from polarized light
abstract
Accurate orientation information is the key in many applications, ranging from map reconstruction with crowdsourcing data, location data analytics, to accurate indoor localization. Many existing solutions rely on noisy magnetic and inertial sensor data, leading to limited accuracy, while others leverage multiple, dense anchor points to improve the accuracy, requiring significant deployment efforts. This paper presents LiCompass, the first system that enables a commodity camera to accurately estimate the object orientation using just a single optical anchor. Our key idea is to allow a camera to observe varying intensity level of polarized light when it is in different orientations and, hence, perform estimation directly from image pixel intensity. As the estimation relies only on pixel intensity, instead of the location of the anchor in an image, the system performs reliably at long distance, with low resolution images, and with large perspective distortion. LiCompass' core designs include an elaborate optical anchor design and a series of signal processing techniques based on trigonometric properties, which extend the range of orientation estimation to full 360 degrees. Our prototype evaluation shows that LiCompass produces very accurate estimates with median errors of merely 2.5 degrees at 5 meters and 7.4 degrees at 2.5 meters with an irradiance angle of 55 degrees.
Yu-Lin Wei, Hsin-I Wu, Han-Chung Wang, Hsin-Mu Tsai, Kate Ching-Ju Lin, Rayana Boubezari, Hoa Le Minh, Zabih Ghassemlooy
INFOCOM6