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Patricia Moore

dblp:198/5014 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none

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

Graphics, computer vision, multimedia, augmented reality and games · 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.

Artificial intelligence
1 paper
3D vision · 100%
Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%

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

TopicWeightPapersLastEvidence papers
Computer vision › 3D vision
3d reconstruction
0.412020
A Smart-Site-Survey System using Image-based 3D Metric Reconstruction and Interactive Panorama Visualization · ACM Multimedia 2020
Visualization and visual analytics › data visualization
panoramic visualization
0.412020
A Smart-Site-Survey System using Image-based 3D Metric Reconstruction and Interactive Panorama Visualization · ACM Multimedia 2020

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

web-based visualization · 0.9image-based reconstruction · 0.9
YearPublicationVenuePosition
2020 A Smart-Site-Survey System using Image-based 3D Metric Reconstruction and Interactive Panorama Visualization
abstract
This work presents a so-called Smart Site Survey (SSS) system that provides an efficient, web-based platform for virtual inspection of remote sites with absolute 3D metrics. Traditional manual surveying requires sending surveyors and specialised measuring tools to the targeted scene, which takes time and requires significant human resource, and often includes human error. The proposed system provides an automated site survey tool. Sample indoor scenes including offices, storage rooms, and laboratory are used for testing purposes, and highly precise virtual scenes are restored, with the measurement accuracy of 1%, i.e. an error ±1.5cm to a 150cm length. This is comparable or superior to existing works or commercial products.
Sha Yu, Kevin McGuinness, Patricia Moore, David Azcona, Noel E. O'Connor
ACM Multimedia3