README
Aria Digital Twin (ADT) Dataset
Figure 1: An overview of the ADT dataset
Dataset Summary
ADT provides raw and synthesized sensor data from Project Aria glasses, combined with groundtruth data generated using a motion capture system including depth images, device trajectories, object trajectories and bounding boxes, and human tracking. We also provide processed sensor data from our Machine Perception Services. Go to ADT Data Format to see a full list of the data we provide.
The ADT dataset contains 236 sequences recording single and dual-person activities. The data was recorded in two spaces: an apartment and a single room office. There are 74 single-instance dynamic objects shared between the two spaces.
Go to the projectaria.com/datasets/adt/ to learn more about the dataset, including instructions for downloading the data, installing our dataset specific tooling, and running example tutorials.
Dataset Contents
ADT contains 236 sequences, each sequence consists of a single Aria device recording (in VRS format) along with all ground truth data that accompanies this recording. When multiple devices were recording data concurrently, they are always time synchronized and all data collected in each scene is expresssed in the same World coordinate frame. Along with ground truth data, we also provide output from our Machine Perception Services (MPS) which you can learn more about here. All data included in each sequences is broken down in the table below:
| Data type | What's included | Per sequence size | Total size for all sequences |
|---|---|---|---|
| main Aria | Aria raw data, 2D bounding box, 3D object poses and bounding box, skeleton data, eye gaze data | 3 - 6 GB | ~700 GB |
| segmentation | Instance segmentation data | 2 - 4 GB | ~750 GB |
| depth | Depth map data | 4 - 8 GB | ~1.5 TB |
| synthetic | Synthetic rendering data | 2 - 4 GB | 500 GB |
| MPS eyegaze | Eyegaze, summary file | < 1 MB | ~31 MB |
| MPS SLAM points | Semi-dense points and observations | 200 - 500 MB | ~31 GB |
| MPS SLAM trajectories | Open and closed loop trajectories | 100 - 200 MB | 12 GB |
| MPS SLAM online calibration | Online calibrations | < 20 MB | 1.2 GB |
Citation Information
If using ADT, please cite our research paper which can be found here.
License
ADT license can be found here.
Contributors
@nickcharron
Contributors
4 commits
Similar repos
README
Aria Digital Twin (ADT) Dataset
Figure 1: An overview of the ADT dataset
Dataset Summary
ADT provides raw and synthesized sensor data from Project Aria glasses, combined with groundtruth data generated using a motion capture system including depth images, device trajectories, object trajectories and bounding boxes, and human tracking. We also provide processed sensor data from our Machine Perception Services. Go to ADT Data Format to see a full list of the data we provide.
The ADT dataset contains 236 sequences recording single and dual-person activities. The data was recorded in two spaces: an apartment and a single room office. There are 74 single-instance dynamic objects shared between the two spaces.
Go to the projectaria.com/datasets/adt/ to learn more about the dataset, including instructions for downloading the data, installing our dataset specific tooling, and running example tutorials.
Dataset Contents
ADT contains 236 sequences, each sequence consists of a single Aria device recording (in VRS format) along with all ground truth data that accompanies this recording. When multiple devices were recording data concurrently, they are always time synchronized and all data collected in each scene is expresssed in the same World coordinate frame. Along with ground truth data, we also provide output from our Machine Perception Services (MPS) which you can learn more about here. All data included in each sequences is broken down in the table below:
| Data type | What's included | Per sequence size | Total size for all sequences |
|---|---|---|---|
| main Aria | Aria raw data, 2D bounding box, 3D object poses and bounding box, skeleton data, eye gaze data | 3 - 6 GB | ~700 GB |
| segmentation | Instance segmentation data | 2 - 4 GB | ~750 GB |
| depth | Depth map data | 4 - 8 GB | ~1.5 TB |
| synthetic | Synthetic rendering data | 2 - 4 GB | 500 GB |
| MPS eyegaze | Eyegaze, summary file | < 1 MB | ~31 MB |
| MPS SLAM points | Semi-dense points and observations | 200 - 500 MB | ~31 GB |
| MPS SLAM trajectories | Open and closed loop trajectories | 100 - 200 MB | 12 GB |
| MPS SLAM online calibration | Online calibrations | < 20 MB | 1.2 GB |
Citation Information
If using ADT, please cite our research paper which can be found here.
License
ADT license can be found here.
Contributors
@nickcharron
Similar repos
Linked in READMEs
Contributors
4 commits