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Hand-pose annotations: measured versus estimated labels
Inspect reference systems, coordinates, uncertainty and processing before treating hand pose as ground truth.
Published 2026-10-27 · 5 min read
| Question | Evidence or decision |
|---|---|
| Provenance | Sensor/reference method, software and review |
| Schema | Joints, representation, units, axes and frame |
| Missingness | Validity, occlusion and uncertainty conventions |
| Validation | Reference subset, metric definition and known failure conditions |
A hand-pose file may contain manually labeled image points, a model estimate, a fitted body representation or a pose derived from a separate tracking system. Its numeric shape does not reveal the evidence behind it.
Ask which quantities were observed and which were inferred. Even a reference-based annotation pipeline includes processing and limitations. A ground-truth label needs an explained reference method and validation, not just confidence scores from the prediction model.
Describe the reference and processing chain
HOT3D documents a motion-capture reference with optical markers for hand and object poses and provides named annotation representations. This is an example of disclosed provenance, not evidence that an arbitrary vendor’s labels use the same process or achieve the same quality.
For each proposed package, identify source sensors, calibration, fitting or estimation software, versions and review. Mark unavailable reference data explicitly. A model trained on a benchmark does not turn its later predictions into that benchmark’s reference annotations.
Make the coordinate schema inspectable
Request joint names and ordering, left/right convention, frame origin, axes, handedness, units and whether values are 2D image points, 3D coordinates, rotations or model parameters. Document camera relationships and timestamp mapping.
Ask how missing, occluded or off-screen hands are represented. A zero-filled pose may look valid numerically while meaning no observation. Require validity flags and distinguish uncertainty from a successful measurement.
Evaluate with task-relevant evidence
Use a relevant held-out reference where available and state how errors are computed, aligned and aggregated. A single mean can hide difficult occlusions or particular task failures. Do not claim a universal millimeter threshold for all applications.
If no reference exists for a proposed collection, say so. Visual review can expose some problems but does not establish metric 3D accuracy on its own. Keep inference confidence, human review and reference-based error as different fields.
Quote labels as a defined deliverable
Separate original observations from estimation, annotation review and any reference capture work. A skeleton file is not proof of contact forces, tactile measurement or robot controls. Match the requested signal to the intended use.
Run a pilot with the delivered schema, calibration and validity fields. Fiund confirms available signals after review and does not treat this guide as a claim of an existing measured-pose inventory. Buyers and owners should describe their actual evidence rather than upgrading estimated labels in a marketing summary.
Frequently asked questions
Does a high model confidence score prove accuracy?
No. Confidence is not a substitute for appropriate reference-based validation.
Does a 3D skeleton prove force or tactile measurements?
No. Those signals require separate source evidence.