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Documenting motion sequences with a personalized annotation system

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3 Author(s)
Kahol, K. ; Arizona State Univ., USA ; Tripathi, P. ; Panchanathan, S.

We present a novel technique for motion annotation that adapts to a person's style and vocabulary of basic movements (gestures). The system segments continuous motion sequences into gestures, which it then documents in a personalized annotation with an intuitive hierarchical representation. Initial testing suggests that software based on this technique could be an effective teaching aid for dance and sports.

Published in:

MultiMedia, IEEE  (Volume:13 ,  Issue: 1 )