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Data on annotated approximate bilaterally symmetric leaf-off trees based on particle flow simulation and predefined tree crown shape()
Trees are natural objects, where deviations through the branches amplify geometric data for 3D representation and bring challenges to various applications dealing with 3D models, such as compression, visualization, symmetry detection, and radiative transfer simulation. This data article describes da...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8762349/ https://www.ncbi.nlm.nih.gov/pubmed/35071704 http://dx.doi.org/10.1016/j.dib.2022.107806 |
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author | Kohek, Štefan Lukač, Niko Strnad, Damjan Kolingerova, Ivana Žalik, Borut |
author_facet | Kohek, Štefan Lukač, Niko Strnad, Damjan Kolingerova, Ivana Žalik, Borut |
author_sort | Kohek, Štefan |
collection | PubMed |
description | Trees are natural objects, where deviations through the branches amplify geometric data for 3D representation and bring challenges to various applications dealing with 3D models, such as compression, visualization, symmetry detection, and radiative transfer simulation. This data article describes dataset of approximately symmetric 3D tree models with manually identified predominant symmetry plane in each tree model. Parameters for procedural tree synthesis were manually adjusted to produce approximately bilaterally symmetric trees which are grouped into species with distinct features. In the last step, each tree was manually annotated with approximate symmetry plane. This dataset contains geometric data of branches, manually defined parameters for tree synthesis method, point clouds, and a division plane with a score of bilateral symmetry strength. The generated trees can be used as benchmark data for verification of approximate reflectional symmetry detection methods. Additionally, generated 3D tree models can be used for other applications requiring pregenerated trees, such as compression of tree models, instancing, decimation methods, and radiative transfer simulation and modeling. |
format | Online Article Text |
id | pubmed-8762349 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-87623492022-01-20 Data on annotated approximate bilaterally symmetric leaf-off trees based on particle flow simulation and predefined tree crown shape() Kohek, Štefan Lukač, Niko Strnad, Damjan Kolingerova, Ivana Žalik, Borut Data Brief Data Article Trees are natural objects, where deviations through the branches amplify geometric data for 3D representation and bring challenges to various applications dealing with 3D models, such as compression, visualization, symmetry detection, and radiative transfer simulation. This data article describes dataset of approximately symmetric 3D tree models with manually identified predominant symmetry plane in each tree model. Parameters for procedural tree synthesis were manually adjusted to produce approximately bilaterally symmetric trees which are grouped into species with distinct features. In the last step, each tree was manually annotated with approximate symmetry plane. This dataset contains geometric data of branches, manually defined parameters for tree synthesis method, point clouds, and a division plane with a score of bilateral symmetry strength. The generated trees can be used as benchmark data for verification of approximate reflectional symmetry detection methods. Additionally, generated 3D tree models can be used for other applications requiring pregenerated trees, such as compression of tree models, instancing, decimation methods, and radiative transfer simulation and modeling. Elsevier 2022-01-10 /pmc/articles/PMC8762349/ /pubmed/35071704 http://dx.doi.org/10.1016/j.dib.2022.107806 Text en © 2022 The Author(s) 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 Kohek, Štefan Lukač, Niko Strnad, Damjan Kolingerova, Ivana Žalik, Borut Data on annotated approximate bilaterally symmetric leaf-off trees based on particle flow simulation and predefined tree crown shape() |
title | Data on annotated approximate bilaterally symmetric leaf-off trees based on particle flow simulation and predefined tree crown shape() |
title_full | Data on annotated approximate bilaterally symmetric leaf-off trees based on particle flow simulation and predefined tree crown shape() |
title_fullStr | Data on annotated approximate bilaterally symmetric leaf-off trees based on particle flow simulation and predefined tree crown shape() |
title_full_unstemmed | Data on annotated approximate bilaterally symmetric leaf-off trees based on particle flow simulation and predefined tree crown shape() |
title_short | Data on annotated approximate bilaterally symmetric leaf-off trees based on particle flow simulation and predefined tree crown shape() |
title_sort | data on annotated approximate bilaterally symmetric leaf-off trees based on particle flow simulation and predefined tree crown shape() |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8762349/ https://www.ncbi.nlm.nih.gov/pubmed/35071704 http://dx.doi.org/10.1016/j.dib.2022.107806 |
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