Person detection, action recognition, anomaly labeling, and privacy-compliant annotation for security and public safety AI applications.
Automated face detection and blurring applied before annotation; PII regions flagged and masked according to GDPR/local privacy regulations; consent status verified per data source.
Camera parameters (FOV, mounting height, angle) documented; scene context classified (indoor/outdoor, lighting, crowd density) for annotator orientation.
Person detection, pose estimation, and activity classification (walking, running, loitering, fighting, falling) with temporal boundaries and confidence indicators.
Rare events (intrusion, abandoned object, crowd surge) labeled with event type, severity, start/end timestamps, and spatial bounding regions.
Person re-identification labels linked across camera views; track IDs maintained through occlusion and camera handoff zones.
Final dataset delivered with privacy compliance documentation: blurring verification log, PII handling report, and GDPR Article 35 DPIA support materials.
Generic annotation vendors can label data. Domain experts label it correctly. Here's why the difference matters in your industry.
Surveillance data contains PII governed by GDPR, CCPA, and local regulations. Our pipeline applies automated face blurring before any human annotator sees the data — with documented compliance workflows that satisfy DPIA requirements.
Anomaly detection models suffer from extreme class imbalance — suspicious events may occur in <0.1% of footage. Our annotators are trained to identify subtle behavioral cues and temporal patterns that generic labelers miss, improving rare-event recall by 40%+.
Person re-identification across camera views requires understanding of spatial layouts, camera handoff zones, and appearance variations due to lighting changes. Our annotators work with facility maps to maintain consistent track IDs across views.
See how our domain-specific capabilities compare to generic annotation services.
| Capability | UTL Data Engine | Typical Vendor |
|---|---|---|
| Automated face blurring before annotation | Pre-pipeline | Post-processing |
| Multi-camera person re-identification | Cross-view linked | Single-camera only |
| Activity classification (10+ action types) | Full taxonomy | 3–5 actions |
| GDPR/privacy compliance documentation | Included | Not provided |
| Thermal + RGB annotation support | Multi-modal | RGB only |
| 24/7 annotation coverage | Global shifts | Business hours |
"Privacy-compliant annotation is table stakes for us. UTL's workflow ensured PII was handled correctly while maintaining high detection accuracy across challenging camera conditions."
Let's discuss your specific data challenges and build a tailored annotation pipeline.
