Dataset Open Access
Indoor3Dmapping dataset
Armando Arturo Sánchez Alcázar;
Giovanni Pintore;
Matteo Sgrenzaroli
DCAT Export
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<dcat:keyword>point cloud</dcat:keyword>
<dcat:keyword>indoor</dcat:keyword>
<dcat:keyword>3D mapping</dcat:keyword>
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<dct:description><p><strong>Data Organization</strong><br> Under the root directory for the whole acquisition, there is a <em>positions.csv</em>&nbsp;file and 3 subdirectories: <em>img</em>, <em>dense</em>, and <em>sparse</em>. The mobile mapping 3D dataset was generated walking around an indoor space and each&nbsp;<strong>&lt;positionID&gt;</strong> corresponds to a unique pose along the trajectory of this motion. This version of the dataset contains a total of 99 unique poses. There is a separation of 1 meter between each adjacent pose.</p> <pre><code>root ├── img │ ├── &lt;positionID&gt;.jpg | └── ... ├── dense │ ├── &lt;positionID&gt;.png | └── ... ├── sparse │ ├── &lt;positionID&gt;.png | └── ... └── positions.csv</code></pre> <p><strong>positions.csv</strong></p> <ul> <li>File format: One ASCII file.</li> <li>File structure Rows: Each image is one record.</li> <li>File structure Columns: Comma separated headers, with exact order described below. <ul> <li>Filename, column 0: Panorama file name as on disk, without file extension.</li> <li>Timestamps, column 1: Absolute time at which the panorama was captured, Decimal notation, without thousands separator (microseconds).</li> <li>X,Y,Z, columns 2 through 4: Position of the panoramic camera in decimal notation, without thousands separator (meters).</li> <li>w,x,y,z, columns 5 through 8: Rotation of the camera, quaternion.</li> </ul> </li> </ul> <p><strong>sparse</strong></p> <ul> <li>Set of equirectangular rendered depth images.</li> <li>1920x960 resolution</li> <li>16-bit grayscale PNG</li> <li>White &rarr; 0 m</li> <li>Black &rarr; &ge; 16 m or absent geometry</li> <li>Occlusions: If a pixel was hit by several rays, only the value of the closest one is represented.&nbsp;</li> </ul> <p><strong>dense</strong></p> <ul> <li>Set of equirectangular rendered depth images.</li> <li>1920x960 resolution</li> <li>16-bit grayscale PNG</li> <li>White &rarr; 0 m</li> <li>Black &rarr; &ge; 16 m or absent geometry</li> <li>Occlusions: If a pixel was hit by several rays, only the value of the closest one is represented.</li> </ul> <p><strong>img</strong><br> A set of equirectangular panoramic images was taken with a 360&deg; color camera in 1920x960 resolution. They follow the same trajectory.</p></dct:description>
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<dct:title>Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication</dct:title>
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131
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| All versions | This version | |
|---|---|---|
| Views | 131 | 131 |
| Downloads | 9 | 9 |
| Data volume | 1.1 GB | 1.1 GB |
| Unique views | 101 | 101 |
| Unique downloads | 9 | 9 |
Indexed in
- Publication date:
- March 18, 2022
- DOI:
-
- Keyword(s):
- point cloud indoor 3D mapping
- Grants:
-
European Commission:
- EVOCATION - Advanced Visual and Geometric Computing for 3D Capture, Display, and Fabrication (813170)
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International