Extrinsic verification
Sensor-to-sensor transforms checked against the data itself.
Multi-sensor alignment done properly
Sensor Fusion and Calibration
Camera, LiDAR and radar annotated as one scene, with calibration verified before a single label is drawn.
Alignment Before Annotation
Fusion datasets fail quietly. A small calibration error produces labels that look right in each sensor alone and disagree when combined — and the resulting model errors get blamed on architecture for months. We verify alignment first, every time.
What Is Included
Temporal synchronisation
Timestamp alignment across sensors with different clocks.
Cross-sensor annotation
One object, one identity, across every sensor that saw it.
Projection validation
Labels checked in every sensor frame they appear in.
Point-cloud registration
Multi-sweep alignment for dense reconstruction.
Calibration diagnostics
Reports on where and how badly alignment drifts.
How We Work
- Check, then label Calibration is validated before annotation starts, not after a complaint.
- Consistent identity The same object carries the same id in every modality.
- Drift monitoring Long recordings are checked for alignment drift over time.
- Numeric acceptance Alignment is accepted on measurements, not on how it looks.
The Controls Behind It
- Reprojection error reported Delivered with the batch, per sensor pair.
- Synchronisation tolerance Agreed up front and enforced at delivery.
- Failed frames flagged Unusable frames are marked, not quietly dropped.
- Reproducible transforms Calibration parameters ship with the data.
Ready When You Are
Tell us what you are building and we will come back with a plan, a sample and a price.