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Indoor visual SLAM dataset with various acquisition modalities
The indoor Visual Simultaneous Localization And Mapping (V-SLAM) dataset with various acquisition modalities has been created to evaluate the impact of acquisition modalities on the Visual SLAM algorithm’s accuracy. The dataset contains different sequences acquired with different modalities, includi...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8552193/ https://www.ncbi.nlm.nih.gov/pubmed/34746344 http://dx.doi.org/10.1016/j.dib.2021.107496 |
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author | El Bouazzaoui, Imad Rodriguez, Sergio Vincke, Bastien El Ouardi, Abdelhafid |
author_facet | El Bouazzaoui, Imad Rodriguez, Sergio Vincke, Bastien El Ouardi, Abdelhafid |
author_sort | El Bouazzaoui, Imad |
collection | PubMed |
description | The indoor Visual Simultaneous Localization And Mapping (V-SLAM) dataset with various acquisition modalities has been created to evaluate the impact of acquisition modalities on the Visual SLAM algorithm’s accuracy. The dataset contains different sequences acquired with different modalities, including RGB, IR, and depth images in passive stereo and active stereo modes. Each sequence is associated with a reference trajectory constructed with an Structure From Motion (SFM) and Multi View Stereo (MVS) library for comparison. Data were collected using an intrinsically calibrated Intel RealSense D435i camera. The RGB/IR and depth data are spatially aligned, and the stereo images are rectified. The dataset includes various areas, some with low brightness, with changes in brightness, wide, narrow and texture. |
format | Online Article Text |
id | pubmed-8552193 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-85521932021-11-04 Indoor visual SLAM dataset with various acquisition modalities El Bouazzaoui, Imad Rodriguez, Sergio Vincke, Bastien El Ouardi, Abdelhafid Data Brief Data Article The indoor Visual Simultaneous Localization And Mapping (V-SLAM) dataset with various acquisition modalities has been created to evaluate the impact of acquisition modalities on the Visual SLAM algorithm’s accuracy. The dataset contains different sequences acquired with different modalities, including RGB, IR, and depth images in passive stereo and active stereo modes. Each sequence is associated with a reference trajectory constructed with an Structure From Motion (SFM) and Multi View Stereo (MVS) library for comparison. Data were collected using an intrinsically calibrated Intel RealSense D435i camera. The RGB/IR and depth data are spatially aligned, and the stereo images are rectified. The dataset includes various areas, some with low brightness, with changes in brightness, wide, narrow and texture. Elsevier 2021-10-19 /pmc/articles/PMC8552193/ /pubmed/34746344 http://dx.doi.org/10.1016/j.dib.2021.107496 Text en © 2021 The Authors 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 El Bouazzaoui, Imad Rodriguez, Sergio Vincke, Bastien El Ouardi, Abdelhafid Indoor visual SLAM dataset with various acquisition modalities |
title | Indoor visual SLAM dataset with various acquisition modalities |
title_full | Indoor visual SLAM dataset with various acquisition modalities |
title_fullStr | Indoor visual SLAM dataset with various acquisition modalities |
title_full_unstemmed | Indoor visual SLAM dataset with various acquisition modalities |
title_short | Indoor visual SLAM dataset with various acquisition modalities |
title_sort | indoor visual slam dataset with various acquisition modalities |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8552193/ https://www.ncbi.nlm.nih.gov/pubmed/34746344 http://dx.doi.org/10.1016/j.dib.2021.107496 |
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