Unverified50% confidenceFactExact time
EgoTouch synchronously collects first-person visuals, both-hand poses, and pressure distribution.
1
Sources
50%
Confidence
Long-term
Relevance
10/15/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedEgoExplorer's contributions include: placing vision, motion, touch, and finger details into the same wearable collection framework; using a calibration-plus-constraint method to demonstrate that sparse sensing can also yield relatively high-quality motion reconstruction; and directly linking the dataset with humanoid retargeting, shortening the path from human demonstration to robot policy.75% similarUnverifiedTouchAnything learns to estimate contact location and pressure distribution from vision.68% similarUnverifiedGesture recognition typically first acquires images through a camera, then uses skin-color segmentation, contour extraction, or deep learning models to locate hand keypoints, and finally maps the hand pose to specific commands.68% similarUnverifiedMEgoVista combines reliable visual observations (frames in which fingers are clearly visible) with temporal continuity and anatomical constraints (such as fingers not being able to teleport and joints having physiological limits on their range of motion) to perform hand reconstruction.67% similar
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