xclean-maps / README.md
Pyassahu's picture
xclean 3-D maps: 8 licence-safe maps (own OAK-D-Lite routes + Rosario CC BY 4.0) (part 4)
901ed0b verified
|
Raw History Blame Contribute Delete
2.12 kB
---
license: cc-by-4.0
pretty_name: xclean 3-D maps
tags:
- slam
- gaussian-splatting
- 3d-reconstruction
- visual-inertial-odometry
---
# xclean 3-D maps
3-D Gaussian-splat maps reconstructed by **Necessity Robotics** with **xclean**, a real-time stereo visual-inertial SLAM
system. They are the map files behind the 3-D viewer on https://necessityrobotics.github.io. Every map uses xclean's own live camera poses,
from the median of three runs on the final board, not ground truth. Each map's `ATTRIBUTION.json` states its limitations
as they are.
| map | source data | source licence |
|---|---|---|
| oak_161834 | Recorded by Necessity Robotics with its own OAK-D-Lite camera. | own data |
| oak_160543 | Recorded by Necessity Robotics with its own OAK-D-Lite camera. | own data |
| oak_164002 | Recorded by Necessity Robotics with its own OAK-D-Lite camera. | own data |
| oak_164424 | Recorded by Necessity Robotics with its own OAK-D-Lite camera. | own data |
| oak_161206 | Recorded by Necessity Robotics with its own OAK-D-Lite camera. | own data |
| rosario_01 | The Rosario Dataset (CIFASIS-CONICET), https://robot.cifasis-conicet.gov.ar/ | CC BY 4.0 |
| rosario_03 | The Rosario Dataset (CIFASIS-CONICET), https://robot.cifasis-conicet.gov.ar/ | CC BY 4.0 |
| rosario_04 | The Rosario Dataset (CIFASIS-CONICET), https://robot.cifasis-conicet.gov.ar/ | CC BY 4.0 |
## Licence and credit
- The maps are released under **CC BY 4.0**.
- Maps made from the Rosario Dataset must also credit the source: "The Rosario Dataset, CIFASIS-CONICET, CC BY 4.0
(Pire et al., IJRR 2019)". The changes: a 3-D map was reconstructed from its images.
- The OAK maps come from Necessity Robotics' own recordings.
## Files per map
- `splats.spz`: the viewer's standard tier.
- `splats_lite.*`: the phone / quick tier.
- `full/splats.ply`: full resolution.
- `points.bin` / `points.json`: the sparse point cloud.
- `traj.json`: the camera path.
- `keyframes/`: small keyframe images.
- `film/`: the fly-through video.
- `ATTRIBUTION.json` and `manifest.json` describe the map.