InLUT3D: Indoor Lodz University of Technology Point Cloud Dataset

<h2>Background</h2> <p>This resource contains Indoor Lodz University of Technology Point Cloud Dataset (<strong>InLUT3D</strong>) - a point cloud dataset tailored for real object classification and both semantic and instance segmentation tasks. Comprising of <strong>321</strong> scans, some areas in the dataset are covered by multiple scans. All of them are captured using the Leica BLK360 scanner.</p> <h2>Train/test split</h2> <p>The datset's authors impose the following train-test split:</p> <table> <tbody> <tr> <td><strong>Split</strong></td> <td><strong>Setup range<br></strong></td> </tr> <tr> <td>train</td> <td>from <em>setup_0&nbsp;</em>to&nbsp;<em>setup_300</em></td> </tr> <tr> <td>test</td> <td>from&nbsp;<em>setup_301&nbsp;</em>to&nbsp;<em>setup_320</em></td> </tr> </tbody> </table> <p>The corresponding setups' objects are recommended for splits for the classificcation task.</p> <h2>Available categories</h2> <p>The points are divided into <strong>18 </strong>distinct categories outlined in the <em>label.yaml</em> file along with their respective codes and colors. Among categories you will find:</p> <ul> <li>ceiling,</li> <li>floor,</li> <li>wall,</li> <li>stairs,</li> <li>column,</li> <li>chair,</li> <li>sofa,</li> <li>table,</li> <li>storage,</li> <li>door,</li> <li>window,</li> <li>plant,</li> <li>dish,</li> <li>wallmounted,</li> <li>device,</li> <li>radiator,</li> <li>lighting,</li> <li>other.</li> </ul> <h2>Challenges</h2> <p>Several challenges are intrinsic to the presented dataset:</p> <ol> <li>Extremely non-uniform categories distribution across the dataset.</li> <li>Presence of virtual images, particularly in reflective surfaces, and data exterior to windows and doors.</li> <li>Occurrence of missing data due to scanning shadows (certain areas were inaccessible to the scanner's laser beam).</li> <li>High point density throughout the dataset.</li> </ol> <h2>Dataset structure</h2> <p>The structure of the dataset is the following:</p> <p>inlut3d.tar.gz/<br>├─ setup_0/<br>│ &nbsp;├─ projection.jpg<br>│ &nbsp;├─ segmentation.jpg<br>│ &nbsp;├─ setup_0.pts<br>├─ setup_1/<br>│ &nbsp;├─ projection.jpg<br>│ &nbsp;├─ segmentation.jpg<br>│ &nbsp;├─ setup_1.pts<br>...</p> <table> <tbody> <tr> <td><strong>projection.jpg</strong></td> <td>A file containing a spherical projection of a corresponding PTS file.</td> </tr> <tr> <td><strong>segmentation.jpg</strong></td> <td>A file with objects marked with unique colours.</td> </tr> <tr> <td><strong>setup_x.pts</strong></td> <td>A file with point cloud int the textual PTS format.</td> </tr> </tbody> </table> <h2>Point characteristic</h2> <p>Each PTS file contains 8 columns:</p> <table> <tbody> <tr> <td><strong>Column ID</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>1</td> <td>X Cartesian coordinate</td> </tr> <tr> <td>2</td> <td>Y Cartesian coordinate</td> </tr> <tr> <td>3</td> <td>Z Cartesian Coordinate</td> </tr> <tr> <td>4</td> <td>Red colour in RGB space in the range [0, 255]</td> </tr> <tr> <td>5</td> <td>Green colour in RGB space in the range [0, 255]</td> </tr> <tr> <td>6</td> <td>Blue colour in RGB space in the range [0, 255]</td> </tr> <tr> <td>7</td> <td>Category code</td> </tr> <tr> <td>8</td> <td>Instance ID</td> </tr> </tbody> </table> <p>&nbsp;</p>