Video Annotation Services

Video models require labels that stay consistent across frames — not just static boxes on still images. Our video annotation services provide object tracking, event detection, activity recognition, and temporal taxonomy tags for surveillance platforms, sports analytics, retail behavior AI, and autonomous vehicle perception stacks.

Why temporal accuracy matters in video ML

ID switches and drift between frames destroy tracker performance in production. Our annotators maintain object identity across sequences, annotate events on timelines, and follow frame-interval QA so your models learn stable temporal patterns.

Video labeling capabilities

Single-object and multi-object tracking; action and event segmentation; pose and keypoint tracks; lane and zone polygons on dashcam footage; person re-identification labels; basket and queue analytics for retail video AI.

Use cases across industries

CCTV threat detection and loitering alerts, football and basketball player tracking, in-store shopper journey analysis, warehouse forklift safety monitoring, and multi-sensor AV rigs capturing urban driving scenes.

Operations at broadcast scale

We staff dedicated video pools with 24/7 coverage for continuous ingest from global camera networks. Projects scale from pilot clips to millions of annotated frames per program without sacrificing review depth.

QA for long-form and multi-camera video

Nth-frame audit sampling, consensus on difficult clips, and automated checks for temporal ID consistency. Safety-critical AV and security workloads receive additional specialist review layers.

Get started

Get frame-accurate video training data with enterprise QA. Tell us your frame rate, camera count, taxonomy, and accuracy targets — we scope video annotation timelines and pricing for your ML roadmap.