2D bounding boxes
Boxes follow each object across frames with a consistent ID, so models learn motion as well as appearance.
Video annotation that follows the action
Frame-by-frame video labeling that helps your AI understand motion, context and behavior, from autonomous driving to retail analytics.
- Object tracking · keypoints · polylines
- Frame-by-frame review
- 98%+ accuracy guarantee
motorway_cam_02.mp4annotation
Tracks · 0 in frameframe 300 / 600
◆ keyframes · boxes appear only while their track is active
model pre-labels · not reviewed, needs correctionauto-detection
Video annotation types
Structure for dynamic scenes
Our annotators specialize in object tracking, event tagging and behavior recognition across complex video streams, bringing structure to dynamic scenes so your AI can act with precision and speed.
Segmentation
Frame-by-frame masks for scenes where exact object boundaries matter.
3D cuboids
Cuboids tracked through video to capture the depth, orientation and movement of vehicles and objects.
Keypoints & landmarks
Body and facial keypoints tracked through motion for pose estimation, sports and fitness analytics.
Line & polyline
Lanes, trajectories and boundaries traced across frames for driving and traffic applications.
Video data collection
Custom footage captured to your scenario list when existing video doesn't cover your edge cases.
Tracking that holds up
Every object keeps its ID, frame after frame
Annotators work on keyframes and verify interpolation in between, so tracks stay consistent through occlusions, lane changes and crowd scenes.
- Keyframe + interpolation workflow
- Re-identification after occlusion
- Event and action tags on the timeline
Per-frame boxes linked into player and ball tracks.
Use cases
Where teams put this data to work
Traffic & ADAS
Vehicle and pedestrian tracks for driver assistance, traffic analytics and incident detection.
Sports analytics
Player, ball and pose tracking for performance breakdowns and broadcast graphics.
Retail footfall
Customer journeys and dwell time across in-store camera views.
Activity recognition
Action and event labels on the timeline for safety and behavior models.
How we work
From pilot to production
We begin with your project scope and goals, annotate each frame using a mix of manual and assisted tools, then run QA reviews and feedback rounds with you before delivering production-ready datasets.
- Step 01
Consult
We review your data, edge cases and success criteria, then write annotation guidelines with you.
- Step 02
Annotate
A trained team labels a pilot batch, following the agreed guidelines to the letter.
- Step 03
Calibrate
You review the pilot. We fold your feedback into the guidelines before scaling up.
- Step 04
Multi-layer QA
Every batch passes peer review, expert QA and automated checks before it leaves us.
- Step 05
Deliver
Labels ship in your format on your schedule, ready to drop into training.
Quality pipeline
Five checkpoints between raw data and your model
98%+
Accuracy guarantee
- 01AnnotatorLabels against your guidelines
- 02Peer reviewA second annotator reviews the work
- 03Expert QASenior reviewer samples and corrects
- 04Automated checksRules catch missing or invalid labels
- 05Client sign-offYou approve before final delivery
Results
Quality you can measure
- Accuracy guarantee
- 98%+Accuracy guarantee
- Returning clients
- 96%Returning clients
- Cost reduction
- 2.5xCost reduction
- Projects completed
- 200+Projects completed
“For our ADAS project, Intellisane AI delivered precise vehicle annotations across diverse traffic scenes, including multiple object classes and occlusion scenarios. Their expertise in automotive data workflows and quality-first mindset helped us pass all validation checks, with timely delivery and professional communication throughout.”
Raphael Lopez
Co-Founder & CTO, Felucca
Related
Fueling video intelligence in transportation, security, sports, healthcare, robotics and more.
FAQ
Questions, answered
Something else on your mind? Email sales@intellisane.ai.
Get started
Let's scope your project
Tell us about your data. We'll come back with a plan and a free pilot batch so you can see the quality first.