Abstract
We propose a novel body-centered interaction system making use of a spherical camera attached to a hand. Its broad and unique field of view enables an all-in-one approach to sensing multiple pieces of contextual information in hand-based spatial interactions: (i) hand location on the body surface, (ii) hand posture, (iii) hand keypoints in certain postures, and (iv) the near-hand environment. The proposed system makes use of a deep-learning approach to perform hand location and posture recognition. The proposed system is capable of achieving high hand location and posture recognition accuracy, 85.0 % and 88.9 % respectively, after collecting sufficient data and training. Our result and example demonstrations show the potential of utilizing 360° cameras for vision-based sensing in context-aware body-centered spatial interactions.
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