Egocentric Video Data Collection for AI Training
Custom egocentric data collection for AI training. Multi-camera wearable rigs (Pico 4 Ultra, ZED, Motion Trackers) and trained capture teams deliver synchronized first-person video and 3D pose data, built around your model and scenarios.
- Leading Data ProvidersAhead of Robotics Trends
- Scalable CollectionCustom Data Collection
- 100%Consented participants
Egocentric Video In Numbers
Egocentric Video Dataset
4,050 hours of first-person video capturing daily activities in real environments.
Highlights:
- 4,050 hours across 13 household scenarios
- Pico 4 Ultra + ZED + motion trackers with synchronized IMU
- Quaternion-based 3D pose for egocentric tracking
- Real homes: kitchens, bathrooms, living rooms
How We Capture
Stereo video, 3D depth, and full-body pose — six streams, all synchronized in real time.Inside Our Capture Setup
Pico 4 Ultra + Motion Trackers + ZED
Pico 4 Ultra + Motion Trackers
How The Data Looks
Every scenario ships as a synchronized multi-modal package — RGB streams, depth maps, skeleton poses, and structured annotations. Open in Rerun or export to your own pipeline.
The market keeps asking for more data, but the data they have is broken. I wanted a setup that would make collection highly relevant relevant — not just for now, but for the future.
- Martinian Letunovsky
- Head of IT Department
Real homes. Real people. Real interactions.
How we run production-grade capture
Every session is a coordinated operation — actor briefing, environment prep, multi-device sync check, and quality review before a single clip ships.
See Exactly What You're Buying
- Format
- .mp4, .rrd, .json
- Madalities
- RGB, Depth, Pose, Hands
- Capture
- Pico 4 Ultra
- AVG Duration
- 2–6 min / scenario
- Annotation
- Scene, Action , Object, Hand pose
- Licence
- Commercial, 100% consented
Data Struggles? Let's Fix That
The problem
- Volume isn’t enough. Plenty of first-person video exists, but most of it is unusable noise.
- 2D data for a 3D problem. Flat GoPro footage with no camera position or lens data — useful only for pretraining.
- Lab setups don’t transfer. Controlled lighting and scripted actors don’t reflect real homes or workplaces.
- No body, no hands. Without skeleton and hand pose, action recognition is guesswork — you see what, never how.
What Unidata delivers
- Curated, ML-ready by default. 15,000+ scenarios across 7 room types and 90+ functional zones, with auto-generated pose data.
- Stereo capture with depth maps. Pico 4 Ultra delivers 6 synchronized streams for real-world 3D and spatial geometry.
- Real + controlled environments. Structured scenarios captured in actual homes and kitchens — real backgrounds, real lighting, real motion.
- Full-body skeleton + hand poses. Motion trackers on hands, feet, and pelvis. Full-body pose out of the box.
Industries
What our clients are saying
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- Andrew
- Head of Client Success
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