Origin Data Lab — Egocentric RGB + IMU Evaluation Sample
Version 1.0.3 · First-party technical evaluation sample
This dataset is a compact public capability demonstration from Origin Data Lab for evaluating an egocentric RGB + IMU capture and delivery workflow.
It contains a short real-world task excerpt together with native and application-level IMU streams, structured task annotations, sanitized capture metadata, integrity records, checksums, and a reproducible Python verifier.
This sample demonstrates a specific released capture package. It does not imply that every Origin Data Lab production project uses the same hardware, rates, schema, or timing method.
Quick Facts
| Item | Released sample |
|---|---|
| Video | 1920 × 1080 |
| Frame rate | 30 fps |
| Frames | 587 |
| Duration | 19.567 s |
| Native accelerometer | 8,028 samples · 410.641 Hz |
| Native gyroscope | 8,028 samples · 410.641 Hz |
| App-level accelerometer | 2,001 samples · 102.353 Hz |
| App-level gyroscope | 1,998 samples · 102.162 Hz |
| Audio | Not included |
| Task category | Food preparation |
| Environment | Domestic kitchen |
| Capture country | South Korea |
The video source was portrait (1080 × 1920) and the public preview was transformed 90° counterclockwise without crop or stretch. IMU axes were not rotated to match the transformed preview.
Repository Contents
capture/
video_preview_aligned_19p55s.mp4
sensors/
app_level_accelerometer_clip.csv
app_level_gyroscope_clip.csv
native_accelerometer_clip.csv
native_gyroscope_clip.csv
annotations/
interaction_events.json
task_structure.json
metadata/
capture_metadata_public.json
quality/
integrity_report.json
verification_output.txt
tools/
verify_odl_sample.py
checksums.sha256
DATA_CARD.md
LICENSE.md
README.md
Sensor Measurements
The released verifier computes stream statistics from sensor_timestamp_ns.
| Stream | Samples | Measured rate | Max interval | Duplicate timestamps | Non-monotonic |
|---|---|---|---|---|---|
| App-level accelerometer | 2,001 | 102.353 Hz | 21.9177 ms | 0 | 0 |
| App-level gyroscope | 1,998 | 102.162 Hz | 21.9177 ms | 0 | 0 |
| Native accelerometer | 8,028 | 410.641 Hz | 2.4360 ms | 0 | 0 |
| Native gyroscope | 8,028 | 410.641 Hz | 2.4360 ms | 0 | 0 |
Cross-stream consistency
For timestamps shared by the application-level and native streams:
- accelerometer timestamp matches: 2,001 / 2,001
- native/app accelerometer scale ratio: 9.806650–9.806651
- gyroscope timestamp matches: 1,998 / 1,998
- native/app gyroscope value ratio: 1.000000
These are measured values from this released excerpt, not nominal device specifications.
Temporal Alignment
RGB and IMU in this public excerpt are software-aligned.
The source session used a software visual–inertial refinement of −446 ms before the public timeline was released.
Post-correction pre-release checks produced:
| Check | Result |
|---|---|
| Visual–inertial Method A | 0 ms · R² 0.798 |
| Visual–inertial Method B | +6 ms · Pearson r 0.929 |
| Method A quarter-window shifts | −4, −2, 0, +2 ms |
| Stated alignment uncertainty | within one 30 fps video frame (33 ms) |
These checks are in-sample pre-release visual–inertial checks.
This sample does not claim:
- hardware synchronization between RGB and IMU;
- guaranteed frame-level synchronization;
- sub-frame synchronization;
- held-out validation of the alignment method.
Coordinate Frame and Units
Public metadata identifies the IMU coordinate frame as:
Android device default; portrait source reference
The IMU axes were not rotated to match the landscape public preview.
For this release:
- application-level accelerometer values are represented in g;
- native accelerometer values are strongly supported as m/s² by the exact 9.80665 cross-stream scale relationship;
- gyroscope values are represented as rad/s;
- native and application-level gyroscope values are identical at matching timestamps.
See metadata/capture_metadata_public.json and DATA_CARD.md for the release-specific caveats.
Structured Task Metadata
The package includes:
annotations/task_structure.jsonannotations/interaction_events.json
These files provide structured task and interaction information for the released excerpt. They are evaluation examples, not universal ontology definitions.
Integrity and Reproducibility
checksums.sha256 provides SHA-256 hashes for the released payload.
The included verifier checks:
- SHA-256 manifest integrity
- per-stream timestamp statistics
- duplicate and non-monotonic timestamps
- application/native cross-stream consistency
- visual–inertial lag between image motion and native gyroscope motion
Run the verifier
pip install numpy opencv-python
python tools/verify_odl_sample.py .
A recorded verifier run is included at:
quality/verification_output.txt
The companion GitHub repository provides the verification tooling and technical documentation:
GitHub: https://github.com/origin-data-lab/egocentric-rgb-imu-sample
Privacy
The public package removes or excludes:
- audio
- exact location
- collector identifiers
- absolute Unix arrival timestamps
- internal capture identifiers
Public field-data releases remain subject to applicable rights, consent, privacy, and project-specific requirements.
Intended Use
This sample is intended for:
- technical evaluation of the released RGB + IMU package;
- inspection of measured sensor characteristics;
- inspection of timing methodology and limitations;
- evaluation of task / interaction metadata structure;
- integrity and reproducibility checks;
- buyer-side discussion of custom Physical AI and robotics data requirements.
It should not be interpreted as a benchmark dataset or as proof of suitability for a particular robot policy, VLA system, world model, or downstream training pipeline without buyer-specific evaluation.
License
This dataset uses the release-specific terms in LICENSE.md.
The license is intentionally marked as other in the Hugging Face metadata because the package uses its own evaluation terms rather than a standard open-source dataset license.
Origin Data Lab
Origin Data Lab produces real-world multimodal training data for Physical AI, robotics, and embodied AI, including field sourcing, worker onboarding, capture operations, sensor and metadata pipelines, QC, recapture, and customer-specific structured delivery.
Technical Field Note:
https://origindatalab.io/technical-field-notes/egocentric-rgb-imu-task-sample.html
Company:
https://origindatalab.io/
Release: v1.0.3
Sample type: capability demonstration
Validation scope: in-sample pre-release visual–inertial checks
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