DenseMatch: a dataset for real-time 3D reconstruction

We provide a database aimed at real-time quantitative analysis of 3D reconstruction and alignment methods, containing 3140 point clouds from 10 subjects/objects. These scenes are acquired with a high-resolution 3D scanner. It contains depth maps that produce point clouds with more than 500k points o...

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Detalles Bibliográficos
Autores principales: Lombardi, Marco, Savardi, Mattia, Signoroni, Alberto
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Data Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8529091/
https://www.ncbi.nlm.nih.gov/pubmed/34712753
http://dx.doi.org/10.1016/j.dib.2021.107476
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author Lombardi, Marco
Savardi, Mattia
Signoroni, Alberto
author_facet Lombardi, Marco
Savardi, Mattia
Signoroni, Alberto
author_sort Lombardi, Marco
collection PubMed
description We provide a database aimed at real-time quantitative analysis of 3D reconstruction and alignment methods, containing 3140 point clouds from 10 subjects/objects. These scenes are acquired with a high-resolution 3D scanner. It contains depth maps that produce point clouds with more than 500k points on average. This dataset is useful to develop new models and alignment strategies to automatically reconstruct 3D scenes from data acquired with optical scanners or benchmarking purposes.
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spelling pubmed-85290912021-10-27 DenseMatch: a dataset for real-time 3D reconstruction Lombardi, Marco Savardi, Mattia Signoroni, Alberto Data Brief Data Article We provide a database aimed at real-time quantitative analysis of 3D reconstruction and alignment methods, containing 3140 point clouds from 10 subjects/objects. These scenes are acquired with a high-resolution 3D scanner. It contains depth maps that produce point clouds with more than 500k points on average. This dataset is useful to develop new models and alignment strategies to automatically reconstruct 3D scenes from data acquired with optical scanners or benchmarking purposes. Elsevier 2021-10-14 /pmc/articles/PMC8529091/ /pubmed/34712753 http://dx.doi.org/10.1016/j.dib.2021.107476 Text en © 2021 Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Data Article
Lombardi, Marco
Savardi, Mattia
Signoroni, Alberto
DenseMatch: a dataset for real-time 3D reconstruction
title DenseMatch: a dataset for real-time 3D reconstruction
title_full DenseMatch: a dataset for real-time 3D reconstruction
title_fullStr DenseMatch: a dataset for real-time 3D reconstruction
title_full_unstemmed DenseMatch: a dataset for real-time 3D reconstruction
title_short DenseMatch: a dataset for real-time 3D reconstruction
title_sort densematch: a dataset for real-time 3d reconstruction
topic Data Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8529091/
https://www.ncbi.nlm.nih.gov/pubmed/34712753
http://dx.doi.org/10.1016/j.dib.2021.107476
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AT savardimattia densematchadatasetforrealtime3dreconstruction
AT signoronialberto densematchadatasetforrealtime3dreconstruction

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