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| license: cc-by-4.0 | |
| pretty_name: Minimal Texture Dataset for RGB-D SLAM | |
| tags: | |
| - slam | |
| - rgbd | |
| - visual-odometry | |
| - robotics | |
| - realsense | |
| # Minimal Texture Dataset for RGB-D SLAM | |
| RGB-D sequences recorded with an Intel RealSense D435i over low-texture conceptual-geometry and | |
| sand scenes at DLR (German Aerospace Center), with millimeter-accurate ground truth from a Vicon | |
| motion-capture system. The dataset was introduced for the evaluation of | |
| [SID-SLAM: Semi-Direct Information-Driven RGB-D SLAM](https://ieeexplore.ieee.org/document/10058038) | |
| (IEEE RA-L, 2023). | |
| This repository is the authoritative re-upload of the dataset previously published on | |
| [Zenodo (10.5281/zenodo.10453700)](https://zenodo.org/records/10453700), regenerated from the | |
| original recordings. It extends the published set with the full first recording session and the | |
| previously unpublished easy sequences. | |
| - Homepage: https://www.dlr.de/en/rm/research/publications-and-downloads/datasets/minimal-texture-dataset-for-rgb-d-slam | |
| - Integrated in [VSLAM-LAB](https://github.com/VSLAM-LAB/VSLAM-LAB) as dataset `minimal` | |
| ## Contents | |
| Sequences are grouped by recording day: | |
| - `10-08/` — first session, 2021-10-08 (15 sequences: parallel_lines, circles, hexagon, triangle, | |
| deformation_model, sand, square_with_circles, and loop variants) | |
| - `10-14/` — second session, 2021-10-14 (18 sequences: the 14 published on Zenodo — triangle, | |
| circle, square, hexagon, dodecagon, lines, the three circle_* loop sequences, sand_rocks — plus | |
| forward_backward_01, circle_only_01, lru_01 and ardea_01) | |
| Each sequence ships two files: | |
| - `<day>/<name>.bag` — ROS1 bag (bz2-compressed) with the RealSense D435i streams: | |
| - `/camera/color/image_raw` — rgb8, 1280x720 @ 30 Hz | |
| - `/camera/aligned_depth_to_color/image_raw` — 16UC1 depth aligned to color, millimeters, 1280x720 @ 30 Hz | |
| - `/camera/color/camera_info`, `/camera/aligned_depth_to_color/camera_info` — intrinsics | |
| - `/camera/imu` — ~200 Hz (camera-to-IMU extrinsics not included) | |
| - `/camera/extrinsics/depth_to_color` | |
| - `<day>/<name>_groundtruth.txt` — Vicon ground-truth trajectory in TUM format | |
| (`timestamp[s] tx ty tz qx qy qz qw`), evaluation-ready, same clock as the bag. | |
| `T_vicon_camera.txt` (repo root) holds the Vicon-marker to `camera_color_optical_frame` extrinsic. | |
| ## Calibration | |
| Color intrinsics (identical for both sessions, zero distortion / plumb_bob, 1280x720): | |
| ``` | |
| fx = 908.479248 fy = 907.841919 | |
| cx = 650.889160 cy = 364.692657 | |
| ``` | |
| The aligned depth stream shares these intrinsics by construction. Depth in meters = value / 1000. | |
| ## Calibration recordings & raw metadata (archive) | |
| The original calibration recordings and per-sequence provenance from the 2021 sessions are | |
| archived here as well (not needed to run the sequences, but preserved as the primary copy): | |
| - `calibration/10-08/` — `timestamps_camera_calibration_seq01.bag`, | |
| `viconMarker_camera_calibration_seq01.bag`, `viconMarker_camera_calibration_seq02.bag` | |
| - `calibration/10-14/` — `deformation_model_calibration.bag`, | |
| `lukas_pattern_calibration_01.bag`, `photo_calibration.bag` | |
| These are the bz2-compressed ROS1 bags used for the Vicon-marker/camera extrinsic | |
| (`T_vicon_camera.txt`), camera-clock/Vicon timestamp calibration, and photometric/pattern | |
| calibration. | |
| - `metadata/10-08.tar.gz`, `metadata/10-14.tar.gz` — the original per-sequence recording folders | |
| (environment and git-version snapshots, `params.yaml`, `tf.cfg`, raw Vicon/tf bags, and | |
| `vicon_direct_features_*.txt`), documenting how each sequence's ground truth was produced. | |
| ## Citation | |
| ```bibtex | |
| @article{fontan2023sid, | |
| title={{SID-SLAM}: Semi-Direct Information-Driven {RGB-D SLAM}}, | |
| author={Font{\'a}n, Alejandro and Giubilato, Riccardo and Oliva, Laura and Civera, Javier and Triebel, Rudolph}, | |
| journal={IEEE Robotics and Automation Letters}, | |
| volume={8}, | |
| number={10}, | |
| pages={6387--6394}, | |
| year={2023} | |
| } | |
| ``` | |
| ## License | |
| [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) | |