What is Egocentric Video Data?
Egocentric Video Data — first-person footage, usually from a head-mounted camera, showing hands and objects from the wearer's own viewpoint.
The camera is the easy part — a head-mounted action camera at 30 to 60 fps — and the annotation is what costs. The labels that matter are hand-object interaction: when a hand enters frame, what it touches, what action it performs. Ego4D, the largest public set, holds about 3,670 hours from 931 camera wearers across 74 locations. EPIC-KITCHENS-100 is smaller and deeper: 100 hours in 45 kitchens, with roughly 90,000 annotated action segments.
What separates egocentric capture from other video is that it records life as it happens, which means it records people who did not agree to appear. Ego4D was collected under a documented de-identification procedure, and commissioned capture needs the same: a written rule for bystanders, applied before delivery.
For robot learning the value is observation without a robot — no platform, no operator, no resets between attempts — which is why egocentric footage scales to hours that teleoperation cannot reach. Capture for a specific task, environment or hand-object domain can be commissioned to order, and the bystander policy belongs in the brief, because it is far cheaper to decide before recording than after.
Related terms
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Motion Capture Data
Motion Capture Data — human body motion recorded as joint trajectories, used for animation and as a reference for robots that imitate people.
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Robot Data Annotation
Robot Data Annotation — attaching labels to robot episodes: what the task was, whether it succeeded, and when key events happened.
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Embodied AI Data
Embodied AI Data — training data for systems that act in the physical world, where every sample records what was perceived, what was done and what happened.
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