Autonomous driving
Track vehicles, pedestrians, and cyclists across dashcam and sensor footage.
Computer Vision
Video Annotation Services
Frame-accurate labeling, object tracking, and event tagging for video understanding models.
Overview
Video multiplies annotation complexity: identity must persist across frames, events have start and end times, and volumes are enormous. Our teams combine interpolation-assisted tooling with human keyframe review to deliver temporally consistent tracks, activity labels, and event annotations at production scale — with per-track QA so identity switches and drift are caught before delivery.
What's included
- ✓Multi-object tracking with persistent IDs
- ✓Frame-by-frame and interpolated bounding boxes/polygons
- ✓Temporal event and activity annotation
- ✓Video classification and scene segmentation
- ✓Ego-centric and multi-camera video labeling
- ✓High-volume pipelines with per-track quality checks
Use cases
Sports analytics
Player tracking, action recognition, and event timelines.
In-cabin monitoring
Driver attention, drowsiness, and occupancy labeling.
Robotics
Manipulation and interaction video data for embodied AI.
How we work
1
Scope & pilot
We review your data, define the labeling guide together, and run a paid pilot batch so you can judge quality before scaling.
2
Team & calibrate
A dedicated, trained team ramps on your guidelines, benchmarked against gold-standard tasks until accuracy targets are hit.
3
Produce & QA
Production batches flow through multi-tier QA — consensus review, statistical sampling, and edge-case escalation.
4
Deliver & iterate
Data ships in your format with accuracy reports. Guidelines evolve with your model's failure cases.
Frequently asked questions
How do you guarantee quality forvideo annotation services?
Every project runs through multi-tier QA: annotators are benchmarked against gold-standard tasks before production, batches are statistically sampled against agreed accuracy targets, and ambiguous cases are escalated and documented in a living labeling guide. You receive accuracy reports with every delivery.
Can we start with a small pilot before committing?
Yes — we recommend it. A paid pilot batch on your real data lets you evaluate our quality, turnaround, and communication before scaling. Pilot learnings become the project's labeling guide.
How is our data kept secure?
Client data is encrypted in transit and at rest, access is limited to the assigned project team under NDAs, and we support VPN-restricted or client-hosted workflows where data cannot leave your environment. Retention and certified deletion terms are set per engagement.
What tools and output formats do you support?
We work in your annotation platform or ours, and deliver in the format your pipeline expects — COCO, YOLO, Pascal VOC, JSON, CSV, or a custom schema — with delivery via API, cloud bucket, or scheduled export.
Ready to scale yourvideo annotation services?
Start with a pilot batch — see our quality on your data before you commit.